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2021

  • Augusto Vega
    Alper Buyuktosunoglu
    Davide Callegaro
    Marco Levorato
    Pradip Bose
    A. Vega, A. Buyuktosunoglu, Davide Callegaro, M. Levorato, and P. Bose, Cloud-Backed Mobile CognitionPower-Efficient Deep Learningin the Autonomous Vehicle Era, Springer Computing, 2021.
    @article{vega-alper-2021-springer,
      author = {Augusto Vega and Alper Buyuktosunoglu and \textbf{Davide Callegaro} and Marco Levorato and Pradip Bose},
      title = {Cloud-Backed Mobile CognitionPower-Efficient Deep Learningin the Autonomous Vehicle Era},
      journal = {Springer Computing},
      year = {2021},
    }
  • Davide Callegaro
    Marco Levorato
    Francesco Restuccia
    D. Callegaro, M. Levorato, and F. Restuccia, SeReMAS: Self-Resilient Mobile Autonomous Systems Through Predictive Edge Computing, in 2021 18th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON), 2021.
    @inproceedings{callegaro-levorato-2021-secon,
      author = {Davide Callegaro and Marco Levorato and Francesco Restuccia},
      title = {SeReMAS: Self-Resilient Mobile Autonomous Systems Through Predictive Edge Computing},
      booktitle = {2021 18th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)},
      volume = {},
      number = {},
      pages = {},
      year = {2021},
      doi = {},
    }
  • Anas Alsoliman
    Marco Levorato
    Qi Alfred Chen
    A. Alsoliman, M. Levorato, and Q. A. Chen, Vision-Based Two-Factor Authentication and Localization Scheme for Autonomous Vehicles, Third International Workshop on Automotive and Autonomous Vehicle Security (part of NDSS), 2021.
    @article{alsoliman-levorato-autosec2021,
      author = {Alsoliman, Anas and Levorato, Marco and Chen, Qi Alfred},
      title = {Vision-Based Two-Factor Authentication and Localization Scheme for Autonomous Vehicles},
      journal = {Third International Workshop on Automotive and Autonomous Vehicle Security (part of NDSS)},
      year = {2021},
    }
  • D. Callegaro
    M. Levorato
    D. Callegaro and M. Levorato, Optimal Edge Computing for Infrastructure-Assisted UAV Systems, IEEE Transactions on Vehicular Technology, vol. 70, no. 2, pp. 1782 – 1792, 2021. Release
    @article{callegaro-levorato-2021-tvt,
      author = {D. {Callegaro} and M. {Levorato}},
      title = {Optimal Edge Computing for Infrastructure-Assisted UAV Systems},
      journal = {IEEE Transactions on Vehicular Technology},
      volume = {70},
      number = {2},
      pages = {1782-1792},
      year = {2021},
      doi = {10.1109/TVT.2021.3051378},
    }
  • Anas Alsoliman
    Giulio Rigoni
    Marco Levorato
    Cristina Pinotti
    Nils Ole Tippenhauer
    Mauro Conti
    A. Alsoliman, G. Rigoni, et al.M. Levorato, C. Pinotti, N. O. Tippenhauer, and M. Conti, COTS Drone Detection using Video Streaming Characteristics, in International Conference on Distributed Computing and Networking 2021, 2021, pp. 166 – 175.
    @inproceedings{alsoliman-rigoni-2021-icdcn,
      author = {Alsoliman, Anas and Rigoni, Giulio and Levorato, Marco and Pinotti, Cristina and Tippenhauer, Nils Ole and Conti, Mauro},
      title = {COTS Drone Detection using Video Streaming Characteristics},
      booktitle = {International Conference on Distributed Computing and Networking 2021},
      pages = {166--175},
      year = {2021},
    }

2020

  • Davide Callegaro
    Yoshitomo Matsubara
    Marco Levorato
    Edge Computing
    Split Computing
    Deep Neural Network
    Markov Decision Processes
    D. Callegaro, Y. Matsubara, and M. Levorato, Optimal Task Allocation for Time-Varying Edge Computing Systems with Split DNNs, in 2020 IEEE Global Communications Conference: Selected Areas in Communications: Internet of Things and Smart Connected Communities (Globecom2020 SAC IoTSCC), Taipei, Taiwan, Dec. 2020.
    @inproceedings{callegaro-matsubara-2020-globecom,
      author = {Davide Callegaro and Yoshitomo Matsubara and Marco Levorato},
      title = {Optimal Task Allocation for {Time-Varying} Edge Computing Systems with
    Split {DNNs}},
      booktitle = {2020 IEEE Global Communications Conference: Selected Areas in
    Communications: Internet of Things and Smart Connected Communities
    (Globecom2020 SAC IoTSCC)},
      address = {Taipei, Taiwan},
      month = dec,
      year = {2020},
      days = {6},
      keyword = {Edge Computing; Split Computing; Deep Neural Network; Markov Decision
    Processes},
    }
  • Y. Matsubara
    D. Callegaro
    S. Baidya
    M. Levorato
    S. Singh
    Y. Matsubara, D. Callegaro, S. Baidya, M. Levorato, and S. Singh, Head Network Distillation: Splitting Distilled Deep Neural Networks for Resource-Constrained Edge Computing Systems, IEEE Access, vol. 8, pp. 212177 – 212193, 2020. CodeRelease
    @article{matsubara-callegaro-2020-access,
      author = {Y. {Matsubara} and D. {Callegaro} and S. {Baidya} and M. {Levorato} and S. {Singh}},
      title = {Head Network Distillation: Splitting Distilled Deep Neural Networks for Resource-Constrained Edge Computing Systems},
      journal = {IEEE Access},
      volume = {8},
      number = {},
      pages = {212177-212193},
      year = {2020},
      doi = {10.1109/ACCESS.2020.3039714},
    }
  • P. Tehrani
    M. Levorato
    P. Tehrani and M. Levorato, Frequency-based Multi Task learning With Attention Mechanism for Fault Detection In Power Systems, in 2020 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), 2020, pp. 1 – 6. Release
    @inproceedings{tehrani-levorato-smartgrid-2020,
      author = {P. {Tehrani} and M. {Levorato}},
      title = {Frequency-based Multi Task learning With Attention Mechanism for Fault Detection In Power Systems},
      booktitle = {2020 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)},
      volume = {},
      number = {},
      pages = {1-6},
      year = {2020},
      doi = {10.1109/SmartGridComm47815.2020.9302968},
    }
  • Kevin Choi
    Luca Bedogni
    Marco Levorato
    K. Choi, L. Bedogni, and M. Levorato, Towards Green Crowdsourced Social Delivery Networks: A Feasibility Study, in GLOBECOM 2020-2020 IEEE Global Communications Conference, IEEE, 2020, pp. 1 – 6.
    @inproceedings{choi-bedogni-globecom-2020,
      author = {Choi, Kevin and Bedogni, Luca and Levorato, Marco},
      title = {Towards Green Crowdsourced Social Delivery Networks: A Feasibility Study},
      booktitle = {GLOBECOM 2020-2020 IEEE Global Communications Conference},
      pages = {1--6},
      organization = {IEEE},
      year = {2020},
    }
  • Delaram Amiri
    Arman Anzanpour
    Iman Azimi
    Marco Levorato
    Pasi Liljeberg
    Nikil Dutt
    Amir M. Rahmani
    abnormality detection
    wearable electronics
    Internet of Things
    Health monitoring
    energy efficiency
    edge/fog computing
    edge-assisted control
    context awareness
    D. Amiri, A. Anzanpour, et al.I. Azimi, M. Levorato, P. Liljeberg, N. Dutt, and A. M. Rahmani, Context-Aware Sensing via Dynamic Programming for Edge-Assisted Wearable Systems, ACM Trans. Comput. Healthcare, vol. 1, no. 2, article no. 7, Mar. 2020. Release

    Healthcare applications supported by the Internet of Things enable personalized monitoring of a patient in everyday settings. Such applications often consist of battery-powered sensors coupled to smart gateways at the edge layer. Smart gateways offer several local computing and storage services (e.g., data aggregation, compression, local decision making), and also provide an opportunity for implementing local closed-loop optimization of different parameters of the sensor layer, particularly energy consumption. To implement efficient optimization methods, information regarding the context and state of patients need to be considered to find opportunities to adjust energy to demanded accuracy. Edge-assisted optimization can manage energy consumption of the sensor layer but may also adversely affect the quality of sensed data, which could compromise the reliable detection of health deterioration risk factors. In this article, we propose two approaches: myopic and Markov decision processes (MDPs)—to consider both energy constraints and risk factor requirements for achieving a twofold goal: energy savings while satisfying accuracy requirements of abnormality detection in a patient’s vital signs. Vital signs, including heart rate, respiration rate, and oxygen saturation, are extracted from a photoplethysmogram signal and errors of extracted features are compared to a ground truth that is modeled as a Gaussian distribution. We control the sensor’s sensing energy to minimize the power consumption while meeting a desired level of satisfactory detection performance. We present experimental results on realistic case studies using a reconfigurable photoplethysmogram sensor in an IoT system, and show that compared to nonadaptive methods, myopic reduces an average of 16.9

    @article{amiri-azimi-acmhealth20,
      author = {Amiri, Delaram and Anzanpour, Arman and Azimi, Iman and Levorato, Marco and Liljeberg, Pasi and Dutt, Nikil and Rahmani, Amir M.},
      title = {Context-Aware Sensing via Dynamic Programming for Edge-Assisted Wearable Systems},
      journal = {ACM Trans. Comput. Healthcare},
      volume = {1},
      number = {2},
      publisher = {Association for Computing Machinery},
      address = {New York, NY, USA},
      month = mar,
      year = {2020},
      articleno = {7},
      doi = {10.1145/3351286},
      issn = {2691-1957},
      issue_date = {April 2020},
      keyword = {abnormality detection, wearable electronics, Internet of Things, Health monitoring, energy efficiency, edge/fog computing, edge-assisted control, context awareness},
      numpages = {25},
      url = {https://doi.org/10.1145/3351286},
    }
  • Arman Anzanpour
    Delaram Amiri
    Iman Azimi
    Marco Levorato
    Nikil Dutt
    Pasi Liljeberg
    Amir M. Rahmani
    edge computing
    Internet of Things
    wearable electronics
    Health monitoring
    early warning score
    edge-assisted control
    A. Anzanpour, D. Amiri, et al.I. Azimi, M. Levorato, N. Dutt, P. Liljeberg, and A. M. Rahmani, Edge-Assisted Control for Healthcare Internet of Things: A Case Study on PPG-Based Early Warning Score, ACM Trans. Internet Things, vol. 2, no. 1, article no. 1, Oct. 2020. Release

    Recent advances in pervasive Internet of Things technologies and edge computing have opened new avenues for development of ubiquitous health monitoring applications. Delivering an acceptable level of usability and accuracy for these healthcare Internet of Things applications requires optimization of both system-driven and data-driven aspects, which are typically done in a disjoint manner. Although decoupled optimization of these processes yields local optima at each level, synergistic coupling of the system and data levels can lead to a holistic solution opening new opportunities for optimization. In this article, we present an edge-assisted resource manager that dynamically controls the fidelity and duration of sensing w.r.t. changes in the patient’s activity and health state, thus fine-tuning the trade-off between energy efficiency and measurement accuracy. The cornerstone of our proposed solution is an intelligent low-latency real-time controller implemented at the edge layer that detects abnormalities in the patient’s condition and accordingly adjusts the sensing parameters of a reconfigurable wireless sensor node. We assess the efficiency of our proposed system via a case study of the photoplethysmography-based medical early warning score system. Our experiments on a real full hardware-software early warning score system reveal up to 49

    @article{anzanpour-amiri-acmiot20,
      author = {Anzanpour, Arman and Amiri, Delaram and Azimi, Iman and Levorato, Marco and Dutt, Nikil and Liljeberg, Pasi and Rahmani, Amir M.},
      title = {Edge-Assisted Control for Healthcare Internet of Things: A Case Study on PPG-Based Early Warning Score},
      journal = {ACM Trans. Internet Things},
      volume = {2},
      number = {1},
      publisher = {Association for Computing Machinery},
      address = {New York, NY, USA},
      month = oct,
      year = {2020},
      articleno = {1},
      doi = {10.1145/3407091},
      issn = {2691-1914},
      issue_date = {February 2021},
      keyword = {edge computing, Internet of Things, wearable electronics, Health monitoring, early warning score, edge-assisted control},
      numpages = {21},
      url = {https://doi.org/10.1145/3407091},
    }
  • Yoshitomo Matsubara
    Marco Levorato
    Y. Matsubara and M. Levorato, Neural Compression and Filtering for Edge-Assisted Real-Time Object Detection in Challenged Networks, in 2020 25th International Conference on Pattern Recognition (ICPR), May 2021, pp. 2272 – 2279. Code

    The edge computing paradigm places compute-capable devices — edge servers — at the network edge to assist mobile devices in executing data analysis tasks. Intuitively, offloading compute-intense tasks to edge servers can reduce their execution time. However, poor conditions of the wireless channel connecting the mobile devices to the edge servers may degrade the overall capture-to-output delay achieved by edge offloading. Herein, we focus on edge computing supporting remote object detection by means of Deep Neural Networks (DNNs), and develop a framework to reduce the amount of data transmitted over the wireless link. The core idea we propose builds on recent approaches splitting DNNs into sections — namely head and tail models — executed by the mobile device and edge server, respectively. The wireless link, then, is used to transport the output of the last layer of the head model to the edge server, instead of the DNN input. Most prior work focuses on classification tasks and leaves the DNN structure unaltered. Herein, our focus is on DNNs for three different object detection tasks, which present a much more convoluted structure, and modify the architecture of the network to: (i) achieve in-network compression by introducing a bottleneck layer in the early layers on the head model, and (ii) prefilter pictures that do not contain objects of interest using a convolutional neural network. Results show that the proposed technique represents an effective intermediate option between local and edge computing in a parameter region where these extreme point solutions fail to provide satisfactory performance.

    @inproceedings{matsubara-levorato-2020-icpr,
      author = {Yoshitomo Matsubara and Marco Levorato},
      title = {Neural Compression and Filtering for Edge-Assisted Real-Time Object Detection in Challenged Networks},
      booktitle = {2020 25th International Conference on Pattern Recognition (ICPR)},
      pages = {2272--2279},
      month = may,
      year = {2021},
    }
  • Yoshitomo Matsubara
    Marco Levorato
    Y. Matsubara and M. Levorato, Split Computing for Complex Object Detectors: Challenges and Preliminary Results, in Proceedings of the 4th International Workshop on Embedded and Mobile Deep Learning, Jul. 2020, pp. 7 – 12.

    Following the trends of mobile and edge computing for DNN models, an intermediate option, split computing, has been attracting attentions from the research community. Previous studies empirically showed that while mobile and edge computing often would be the best options in terms of total inference time, there are some scenarios where split computing methods can achieve shorter inference time. All the proposed split computing approaches, however, focus on image classification tasks, and most are assessed with small datasets that are far from the practical scenarios. In this paper, we discuss the challenges in developing split computing methods for powerful R-CNN object detectors trained on a large dataset, COCO 2017. We extensively analyze the object detectors in terms of layer-wise tensor size and model size, and show that naive split computing methods would not reduce inference time. To the best of our knowledge, this is the first study to inject small bottlenecks to such object detectors and unveil the potential of a split computing approach.

    @inproceedings{matsubara-levorato-2020-emdl,
      author = {Yoshitomo Matsubara and Marco Levorato},
      title = {Split Computing for Complex Object Detectors: Challenges and Preliminary Results},
      booktitle = {Proceedings of the 4th International Workshop on Embedded and Mobile Deep Learning},
      pages = {7--12},
      month = jul,
      year = {2020},
    }
  • Davide Callegaro
    Sabur Baidya
    Marco Levorato
    D. Callegaro, S. Baidya, and M. Levorato, Dynamic Distributed Computing for Infrastructure-Assisted Autonomous UAVs, in Proceedings of the IEEE International Conference on Communications (ICC), Dublin, Ireland, Jun. 2020, SAC Tactile Internet Track. Release

    The analysis of information rich signals is at the core of autonomy. In airborne devices such as Unmanned Aerial Vehicles (UAV), the hardware limitations imposed by the weight constraints make the continuous execution of these algorithms challenging. Edge computing can mitigate such limitations and boost the system and mission performance of the UAVs. However, due to the UAVs motion characteristics and complex dynamics of urban environments, remote processing-control loops can quickly degrade. This paper presents Hydra, a framework for the dynamic selection of communication/computation resources in this challenging environment. A full — open-source — implementation of Hydra is discussed and tested via real-world experiments.

    @inproceedings{callegaro-baidya-2020-icc,
      author = {Davide Callegaro and Sabur Baidya and Marco Levorato},
      title = {Dynamic Distributed Computing for Infrastructure-Assisted Autonomous {UAVs}},
      booktitle = {Proceedings of the IEEE International Conference on Communications (ICC)},
      note = {SAC Tactile Internet Track},
      address = {Dublin, Ireland},
      month = jun,
      year = {2020},
      doi = {10.1109/icc40277.2020.9148986},
    }
  • S. Baidya
    P. Tehrani
    M. Levorato
    S. Baidya, P. Tehrani, and M. Levorato, Data-Driven Path Selection for Real-Time Video Streaming at the Network Edge, in 2020 IEEE International Conference on Communications Workshops (ICC Workshops), 2020, pp. 1 – 6. Release
    @inproceedings{baidya-tehrani-2020-icc,
      author = {S. {Baidya} and P. {Tehrani} and M. {Levorato}},
      title = {Data-Driven Path Selection for Real-Time Video Streaming at the Network Edge},
      booktitle = {2020 IEEE International Conference on Communications Workshops (ICC Workshops)},
      volume = {},
      number = {},
      pages = {1-6},
      year = {2020},
      doi = {10.1109/ICCWorkshops49005.2020.9145158},
    }
  • Anas Alsoliman
    Abdulrahman Bin Rabiah
    Marco Levorato
    A. Alsoliman, A. B. Rabiah, and M. Levorato, Privacy-Preserving Authentication Framework for UAS Traffic Management Systems, in 2020 4th Cyber Security in Networking Conference (CSNet), IEEE, 2020, pp. 1 – 8.
    @inproceedings{alsoliman-rabiah-2020-csnet,
      author = {Alsoliman, Anas and Rabiah, Abdulrahman Bin and Levorato, Marco},
      title = {Privacy-Preserving Authentication Framework for UAS Traffic Management Systems},
      booktitle = {2020 4th Cyber Security in Networking Conference (CSNet)},
      pages = {1--8},
      organization = {IEEE},
      year = {2020},
    }

2019

  • H. Choi
    W. Shin
    M. Levorato
    H. V. Poor
    H. Choi, W. Shin, M. Levorato, and H. V. Poor, Harvest-Or-Access: Slotted ALOHA for Wireless Powered Communication Networks, IEEE Transactions on Vehicular Technology, vol. 68, no. 11, pp. 11394 – 11398, 2019. Release
    @article{choi-shin-tvt2019,
      author = {H. {Choi} and W. {Shin} and M. {Levorato} and H. V. {Poor}},
      title = {Harvest-Or-Access: Slotted ALOHA for Wireless Powered Communication Networks},
      journal = {IEEE Transactions on Vehicular Technology},
      volume = {68},
      number = {11},
      pages = {11394-11398},
      year = {2019},
      doi = {10.1109/TVT.2019.2934439},
    }
  • Davide Callegaro
    Sabur Baidya
    Gowri Ramachandran
    Bhaskar Krishnamachari
    Marco Levorato
    Edge computing
    Object detection
    Unmanned Aerial Vehicles
    Wireless networks
    D. Callegaro, S. Baidya, G. Ramachandran, B. Krishnamachari, and M. Levorato, Information Autonomy: Self-Adaptive Information Management for Edge-Assisted Autonomous UAV Systems, in Proceedings of the IEEE Military Communication Conference (MILCOM), Norfolk, VA, Nov. 2019. Release

    Making Unmanned Aerial Vehicles (UAV) fully autonomous faces many challenges, some of which are connected to the inherent limitations of their on-board resources, such as energy supply, sensing capabilities, wireless characteristics, and computational power. The sensing, communication, and computation Internet of Things (IoT) infrastructure surrounding the UAVs can mitigate such limitations. However, external traffic dynamics, signal propagation, and other poignant characteristics of the IoT infrastructure make it an extremely dynamic and incoherent environment, especially in urban scenarios, thus challenging the use of IoT resources for mission-critical UAV applications. Herein, the concept of information autonomy is introduced to extend autonomy to encompass how information-related tasks are handled in this challenging scenario. In this paper, we motivate the need for “Information Autonomy” based on our observations from real-world experiments and present a self-adaptive framework for edge-assisted UAV applications. Through our preliminary evaluation, we show that our “Information Autonomy” framework is capable of handling uncertainties autonomously during run-time.

    @inproceedings{callegaro-baidya-2019-milcom,
      author = {Davide Callegaro and Sabur Baidya and Gowri Ramachandran and Bhaskar Krishnamachari and Marco Levorato},
      title = {Information Autonomy: Self-Adaptive Information Management for Edge-Assisted Autonomous {UAV} Systems},
      booktitle = {Proceedings of the IEEE Military Communication Conference (MILCOM)},
      address = {Norfolk, VA},
      month = nov,
      year = {2019},
      doi = {10.1109/milcom47813.2019.9020956},
      keyword = {Edge computing, Object detection, Unmanned Aerial Vehicles, Wireless networks},
    }
  • Yoshitomo Matsubara
    Sabur Baidya
    Davide Callegaro
    Marco Levorato
    Sameer Singh
    Information Systems
    Mobile Information Processing Systems
    Multimedia Streaming
    Y. Matsubara, S. Baidya, D. Callegaro, M. Levorato, and S. Singh, Distilled Split Deep Neural Networks for Edge-Assisted Real-Time Systems, in Proceedings of the ACM International Conference on Mobile Computing and Networking (MobiCom), Los Cabos, Mexico, Oct. 2019, Workshop on Hot Topics in Video Analytics and Intelligent Edges. CodeRelease

    Offloading the execution of complex Deep Neural Networks (DNNs) models to compute-capable devices at the network edge, that is, edge servers, can significantly reduce capture-to-output delay. However, the communication link between the mobile devices and edge servers can become the bottleneck when channel conditions are poor. We propose a framework to split DNNs for image processing and minimize capture-to-output delay in a wide range of network conditions and computing parameters. The core idea is to split the DNN models into head and tail models, where the two sections are deployed at the mobile device and edge server, respectively. Different from prior literature presenting DNN splitting frameworks, we distill the architecture of the head DNN to reduce its computational complexity and introduce a bottleneck, thus minimizing processing load at the mobile device as well as the amount of wirelessly transferred data. Our results show 98% reduction in used bandwidth and 85% in computation load compared to straightforward splitting.

    @inproceedings{matsubara-baidya-2019-mobicom,
      author = {Yoshitomo Matsubara and Sabur Baidya and Davide Callegaro and Marco Levorato and Sameer Singh},
      title = {Distilled Split Deep Neural Networks for Edge-Assisted Real-Time Systems},
      booktitle = {Proceedings of the ACM International Conference on Mobile Computing and Networking (MobiCom)},
      note = {Workshop on Hot Topics in Video Analytics and Intelligent Edges},
      address = {Los Cabos, Mexico},
      month = oct,
      year = {2019},
      doi = {10.1145/3349614.3356022},
      keyword = {Information Systems, Mobile Information Processing Systems, Multimedia Streaming},
    }
  • MyungJae Shin
    Joongheon Kim
    Marco Levorato
    M. Shin, J. Kim, and M. Levorato, Auction-based charging scheduling with deep learning framework for multi-drone networks, IEEE Transactions on Vehicular Technology, vol. 68, no. 5, pp. 4235 – 4248, 2019.
    @article{shin-kim-tvt2019,
      author = {Shin, MyungJae and Kim, Joongheon and Levorato, Marco},
      title = {Auction-based charging scheduling with deep learning framework for multi-drone networks},
      journal = {IEEE Transactions on Vehicular Technology},
      volume = {68},
      number = {5},
      pages = {4235--4248},
      publisher = {IEEE},
      year = {2019},
    }
  • I. Bisio
    C. Garibotto
    F. Lavagetto
    M. Levorato
    A. Sciarrone
    I. Bisio, C. Garibotto, F. Lavagetto, M. Levorato, and A. Sciarrone, Statistical Analysis of Wireless Traffic: An Adversarial Approach to Drone Surveillance, in 2019 IEEE Global Communications Conference (GLOBECOM), 2019, pp. 1 – 6. Release
    @inproceedings{bisio-garibotto-globecom-2019,
      author = {I. {Bisio} and C. {Garibotto} and F. {Lavagetto} and M. {Levorato} and A. {Sciarrone}},
      title = {Statistical Analysis of Wireless Traffic: An Adversarial Approach to Drone Surveillance},
      booktitle = {2019 IEEE Global Communications Conference (GLOBECOM)},
      volume = {},
      number = {},
      pages = {1-6},
      year = {2019},
      doi = {10.1109/GLOBECOM38437.2019.9013562},
    }
  • Davide Callegaro
    Sabur Baidya
    Marco Levorato
    D. Callegaro, S. Baidya, and M. Levorato, A Measurement Study on Edge Computing for Autonomous UAVs, in Proceedings of the Workshop on Mobile Air-Ground Edge Computing, Systems, Networks, and Applications (MAGESys), Beijing, China, Aug. 2019, in conjunction with the ACM Special Interest Group on Data Communication (SIGCOMM) Conference. Release

    The ability to execute complex signal processing and machine learning tasks in real-time is the core of autonomy. In airborne devices such as Unmanned Aerial Vehicles (UAV), the hardware limitations imposed by the weight constraint make the continuous execution of these algorithms challenging. Edge and fog computing can mitigate such limitations and boost the system and mission-level performance of the UAVs. However, due to the UAVs motion characteristics and complex dynamics of urban environments, the performance of pipelines using interconnected, rather than onboard, resources can quickly degrade. Motivated by the development of Hydra, an architecture for the establishment of flexible sensing-analysis-control pipelines over autonomous airborne systems, this paper reports a preliminary measurement study on the performance of computing task offloading on available network technologies in this class of applications and systems.

    @inproceedings{callegaro-baidya-2019-magesys,
      author = {Davide Callegaro and Sabur Baidya and Marco Levorato},
      title = {A Measurement Study on Edge Computing for Autonomous {UAVs}},
      booktitle = {Proceedings of the Workshop on Mobile Air-Ground Edge Computing, Systems, Networks, and Applications (MAGESys)},
      note = {in conjunction with the ACM Special Interest Group on Data Communication (SIGCOMM) Conference},
      address = {Beijing, China},
      month = aug,
      year = {2019},
      doi = {10.1145/3341568.3342109},
    }
  • R. Valentini
    R. Alesii
    M. Levorato
    F. Santucci
    R. Valentini, R. Alesii, M. Levorato, and F. Santucci, Cross-Layer Analysis of RFID Systems with Correlated Shadowing and Random Radiation Efficiency, in ICC 2019 - 2019 IEEE International Conference on Communications (ICC), 2019, pp. 1 – 7. Release
    @inproceedings{valentini-alesii-icc-2019,
      author = {R. {Valentini} and R. {Alesii} and M. {Levorato} and F. {Santucci}},
      title = {Cross-Layer Analysis of RFID Systems with Correlated Shadowing and Random Radiation Efficiency},
      booktitle = {ICC 2019 - 2019 IEEE International Conference on Communications (ICC)},
      volume = {},
      number = {},
      pages = {1-7},
      year = {2019},
      doi = {10.1109/ICC.2019.8761060},
    }
  • Igor Burago
    Marco Levorato
    I. Burago and M. Levorato, Cloud-Assisted On-Sensor Observation Classification in Latency-Impeded IoT Systems, in Proceedings of the IEEE International Symposium on Information Theory (ISIT), Paris, France, Jul. 2019. Slide DeckRelease

    The combination of computation and communication constraints within the Internet of Things systems require intelligent allocation of decision making and learning processes across a network of sensing and computing devices. In this paper, we present the problem of observation selection for reactive on-sensor decision-making, where the most accurate decision rule cannot be used unaided neither at the sensor (due to limited computing power), nor in the cloud (due to high communication latency). To make time-sensitive adaptation possible in these conditions, we consider learning a decision rule that is computationally viable for on-sensor use and is continuously adjusted by the cloud using the optimal decision rule for supervision. We pose a constrained stochastic optimization problem for online learning of such instrumental on-sensor classifier, propose an algorithm for updating its parameters, and establish the conditions under which convergence to a local extremum is guaranteed, at least for samples of independent observations.

    @inproceedings{burago-levorato-2019-isit,
      author = {Igor Burago and Marco Levorato},
      title = {Cloud-Assisted On-Sensor Observation Classification in Latency-Impeded {IoT} Systems},
      booktitle = {Proceedings of the IEEE International Symposium on Information Theory (ISIT)},
      address = {Paris, France},
      month = jul,
      year = {2019},
      doi = {10.1109/isit.2019.8849760},
    }
  • Korosh Vatanparvar
    Sina Faezi
    Igor Burago
    Marco Levorato
    Mohammad Abdullah Al Faruque
    K. Vatanparvar, S. Faezi, I. Burago, M. Levorato, and M. A. Al Faruque, Extended Range Electric Vehicle With Driving Behavior Estimation in Energy Management, IEEE Transactions on Smart Grid, vol. 10, no. 3, pp. 2959 – 2968, May 2019. Release

    Battery and energy management methodologies have been proposed to address the design challenges of driving range and battery lifetime in Electric Vehicles (EV). However, the driving behavior is a major factor which has been neglected in these methodologies. In this paper, we propose a novel context-aware methodology to estimate the driving behavior in terms of future vehicle speeds and integrate this capability into EV energy management. We implement a driving behavior model using a variation of Artificial Neural Networks (ANN) called Nonlinear AutoRegressive model with eXogenous Inputs (NARX). We train our novel context-aware NARX model based on historical behavior of real drivers, their recent driving reactions, and route average speed retrieved from Google Maps in order to enable driver-specific and self-adaptive driving behavior modeling and long-term estimation. We analyze the estimation error of our methodology and its impact on a battery lifetime-aware automotive climate control, comparing to the state-of-the-art methodologies for various estimation window sizes. Our methodology shows only 12% error for up to 30-second speed prediction which is an improvement of 27% compared to the state-of-the-art. Therefore, the higher accuracy helps the controller to achieve up to 82% of the maximum energy saving and battery lifetime improvement achievable in ideal methodology where the future vehicle speeds are known.

    @article{vatanparvar-faezi-2019-tsg,
      author = {Korosh Vatanparvar and Sina Faezi and Igor Burago and Marco Levorato and Mohammad Abdullah {Al~Faruque}},
      title = {Extended Range Electric Vehicle With Driving Behavior Estimation in Energy Management},
      journal = {IEEE Transactions on Smart Grid},
      volume = {10},
      number = {3},
      pages = {2959--2968},
      month = may,
      year = {2019},
      doi = {10.1109/tsg.2018.2815689},
    }

2018

  • Delaram Amiri
    Arman Anzanpour
    Iman Azimi
    Marco Levorato
    Amir M. Rahmani
    Pasi Liljeberg
    Nikil Dutt
    D. Amiri, A. Anzanpour, et al.I. Azimi, M. Levorato, A. M. Rahmani, P. Liljeberg, and N. Dutt, Edge-Assisted Sensor Control in Healthcare IoT, in Proceedings of the IEEE Global Communications Conference (GLOBECOM), Abu Dhabi, United Arab Emirates, Dec. 2018. Release

    The Internet of Things is a key enabler of mobile health-care applications. However, the inherent constraints of mobile devices, such as limited availability of energy, can impair their ability to produce accurate data and, in turn, degrade the output of algorithms processing them in real-time to evaluate the patient’s state. This paper presents an edge-assisted framework, where models and control generated by an edge server inform the sensing parameters of mobile sensors. The objective is to maximize the probability that anomalies in the collected signals are detected over extensive periods of time under battery-imposed constraints. Although the proposed concept is general, the control framework is made specific to a use-case where vital signs — heart rate, respiration rate and oxygen saturation — are extracted from a Photoplethysmogram (PPG) signal to detect anomalies in real-time. Experimental results show a 16.9% reduction in sensing energy consumption in comparison to a constant energy consumption with the maximum misdetection probability of 0.17 in a 24-hour health monitoring system.

    @inproceedings{amiri-anzanpour-2018-globecom,
      author = {Delaram Amiri and Arman Anzanpour and Iman Azimi and Marco Levorato and Amir M. Rahmani and Pasi Liljeberg and Nikil Dutt},
      title = {Edge-Assisted Sensor Control in Healthcare {IoT}},
      booktitle = {Proceedings of the IEEE Global Communications Conference (GLOBECOM)},
      address = {Abu Dhabi, United Arab Emirates},
      month = dec,
      year = {2018},
      doi = {10.1109/glocom.2018.8647457},
    }
  • Davide Callegaro
    Marco Levorato
    D. Callegaro and M. Levorato, Optimal Computation Offloading in Edge-Assisted UAV Systems, in Proceedings of the IEEE Global Communications Conference (GLOBECOM), Abu Dhabi, United Arab Emirates, Dec. 2018. Release

    The ability of Unmanned Aerial Vehicles (UAV) to autonomously operate is constrained by the severe limitations of on-board resources. The limited processing speed and energy storage of these devices inevitably makes the real-time analysis of complex signals — the key to autonomy — challenging. In urban environments, the UAV can leverage the communication and computation resources of the surrounding city-wide Internet of Things infrastructure to enhance their capabilities. For instance, the UAVs can interconnect with edge computing resources and offload computation task to improve response time to sensor input and reduce energy consumption. However, the complexity of the urban topology and the large number of devices and data streams competing for the same network and computation resources create an extremely dynamic environment, where poor channel conditions and edge server congestion may penalize the performance of task offloading. This paper develops a framework enabling optimal offloading decisions as a function of network and computation load parameters and current state. The optimization is formulated as an optimal stopping time problem over a Markov process.

    @inproceedings{callegaro-levorato-2018-globecom,
      author = {Davide Callegaro and Marco Levorato},
      title = {Optimal Computation Offloading in Edge-Assisted {UAV} Systems},
      booktitle = {Proceedings of the IEEE Global Communications Conference (GLOBECOM)},
      address = {Abu Dhabi, United Arab Emirates},
      month = dec,
      year = {2018},
      doi = {10.1109/glocom.2018.8648099},
    }
  • Max Willian Soares Lima
    Horacio B. Fernandes de Oliveira
    Eulanda Miranda dos Santos
    Edleno Silva de Moura
    Rafael Kohler Costa
    Marco Levorato
    M. W. Soares Lima, H. A. B. Fernandes de Oliveira, et al.E. M. dos Santos, E. S. de Moura, R. K. Costa, and M. Levorato, Efficient and Robust WiFi Indoor Positioning Using Hierarchical Navigable Small World Graphs, in Proceedings of the IEEE International Symposium on Network Computing and Applications (NCA), Cambridge, MA, Nov. 2018. Release

    Indoor positioning systems consist of identifying the physical location of devices inside buildings. They are usually based on the signal strength of a device packet received by a set of WiFi access points. Among the most precise solutions, are those based on machine learning algorithms, such as kNN (k-Nearest Neighbors). This technique is known as fingerprint positioning. Even though kNN is one of the most used classification methods due to its high precision results, it lacks scalability since an instance we need to classify must be compared to all other instances in the training base. In this work, we use a novel hierarchical navigable small world graph technique to fit the training database so that the samples can be efficiently classified in the online phase of the fingerprint positioning, allowing it to be used in large-scale scenarios and/or to be executed in resource-limited devices. We evaluated the performance of this solution using both synthetic and real-world training data and compared its performance to other known kNN variants such as kd-tree and ball-tree. Our results clearly show the performance gains of the graph-based solution, while still being able to maintain or even reduce the positioning error.

    @inproceedings{lima-oliveira-2018-nca,
      author = {Max Willian {Soares Lima} and Horacio A. B. {Fernandes de Oliveira} and Eulanda Miranda {dos Santos} and Edleno Silva {de Moura} and Rafael Kohler {Costa} and Marco Levorato},
      title = {Efficient and Robust {WiFi} Indoor Positioning Using Hierarchical Navigable Small World Graphs},
      booktitle = {Proceedings of the IEEE International Symposium on Network Computing and Applications (NCA)},
      address = {Cambridge, MA},
      month = nov,
      year = {2018},
      doi = {10.1109/nca.2018.8548076},
    }
  • Sabur Baidya
    Zoheb Shaikh
    Marco Levorato
    S. Baidya, Z. Shaikh, and M. Levorato, FlyNetSim: An Open Source Synchronized UAV Network Simulator Based on ns-3 and Ardupilot, in Proceedings of the ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM), Montreal, Canada, Oct. – Nov. 2018. Release

    Unmanned Aerial Vehicle (UAV) systems are being increasingly used in a broad range of applications requiring extensive communications, either to interconnect the UAVs with each other or with ground resources. Focusing either on the modeling of UAV operations or communication and network dynamics, available simulation tools fail to capture the complex interdependencies between these two aspects of the problem. The main contribution of this paper is a flexible and scalable open source simulator — FlyNetSim — bridging the two domains. The overall objective is to enable simulation and evaluation of UAV swarms operating within articulated multi-layered technological ecosystems, such as the Urban Internet of Things (IoT). To this aim, FlyNetSim interfaces two open source tools, ArduPilot and ns-3, creating individual data paths between the devices operating in the system using a publish and subscribe-based middleware. The capabilities of FlyNetSim are illustrated through several case-study scenarios including UAVs interconnecting with a multi-technology communication infrastructure and intra-swarm ad-hoc communications.

    @inproceedings{baidya-shaikh-2018-mswim,
      author = {Sabur Baidya and Zoheb Shaikh and Marco Levorato},
      title = {{FlyNetSim}: An Open Source Synchronized {UAV} Network Simulator Based on {ns-3} and {Ardupilot}},
      booktitle = {Proceedings of the ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM)},
      address = {Montreal, Canada},
      month = oct # {--} # nov,
      year = {2018},
      doi = {10.1145/3242102.3242118},
    }
  • Roberto Valentini
    Marco Levorato
    Fortunato Santucci
    R. Valentini, M. Levorato, and F. Santucci, Optimal aging–aware channel access and power allocation for battery–powered devices with radio frequency energy harvesting, IEEE Transactions on Communications, vol. 66, no. 11, pp. 5773 – 5787, 2018.
    @article{valentini-levorato-tcomm2018,
      author = {Valentini, Roberto and Levorato, Marco and Santucci, Fortunato},
      title = {Optimal aging--aware channel access and power allocation for battery--powered devices with radio frequency energy harvesting},
      journal = {IEEE Transactions on Communications},
      volume = {66},
      number = {11},
      pages = {5773--5787},
      publisher = {IEEE},
      year = {2018},
    }
  • Igor Burago
    Marco Levorato
    I. Burago and M. Levorato, Randomized Edge-Assisted On-Sensor Information Selection for Bandwidth-Constrained Systems, in Proceedings of the Asilomar Conference on Signals, Systems, and Computers (ACSSC), Pacific Groove, California, Oct. 2018. PosterSlide DeckRelease

    The problem of intelligent information selection in the Internet-of-Things systems with limited computational and communication resources is studied. One distinctive property of such systems is the clash of the computational complexity of the desired selection procedure and the low throughput of the wireless links between the devices acquiring information (sensors) and processing it (edge and cloud computing servers). To adaptively resolve that conflict, we propose a stochastic optimization algorithm for edge-assisted online learning of the optimal on-sensor observation classification and transmission decision rules. Using the stochastic Lyapunov function method, we prove that the resulting adaptive procedure can be used to adjust the parameters of the two local decision rules to asymptotically satisfy the constraint on channel access probability and to minimize the expected classification error.

    @inproceedings{burago-levorato-2018-acssc,
      author = {Igor Burago and Marco Levorato},
      title = {Randomized Edge-Assisted On-Sensor Information Selection for Bandwidth-Constrained Systems},
      booktitle = {Proceedings of the Asilomar Conference on Signals, Systems, and Computers (ACSSC)},
      address = {Pacific Groove, California},
      month = oct,
      year = {2018},
      doi = {10.1109/acssc.2018.8645182},
    }
  • Sabur Baidya
    Marco Levorato
    S. Baidya and M. Levorato, Content-Aware Cognitive Interference Control for Urban IoT Systems, IEEE Transactions on Cognitive Communications and Networking, vol. 4, no. 3, pp. 500 – 512, Sep. 2018. Release

    A novel cognitive interference control framework for heterogeneous local access networks supporting computing and data processing in Urban Internet of Things (IoT) systems is presented. The notion of cognitive content-aware interference control is introduced, where the transmission pattern of cognitive nodes is dynamically adapted to the state of “protected” IoT data streams. The state describes the performance degradation that interference would cause to algorithms processing the data if the cognitive nodes would chose to transmit in the corresponding time period. The framework is instantiated for a case-study scenario where Device-to-Device and Long-Term Evolution communications coexist on the same channel resource. A city-monitoring application is considered, where the state captures the type of frames within a multimedia video stream processed at the edge of the network to detect and track objects. Numerical results show that the proposed cognitive transmission strategy enables a significant throughput increase of local D2D communications for a target accuracy of the monitoring application.

    @article{baidya-levorato-2018-tccn,
      author = {Sabur Baidya and Marco Levorato},
      title = {Content-Aware Cognitive Interference Control for Urban {IoT} Systems},
      journal = {IEEE Transactions on Cognitive Communications and Networking},
      volume = {4},
      number = {3},
      pages = {500--512},
      month = sep,
      year = {2018},
      doi = {10.1109/tccn.2018.2815604},
    }
  • Kisong Lee
    Jun-Pyo Hong
    Hyun-Ho Choi
    Marco Levorato
    K. Lee, J.-P. Hong, H.-H. Choi, and M. Levorato, Adaptive Wireless-Powered Relaying Schemes With Cooperative Jamming for Two-Hop Secure Communication, IEEE Internet of Things Journal, vol. 5, no. 4, pp. 2793 – 2803, Aug. 2018. Release

    A two-hop relay network is considered, in which an eavesdropper can overhear the relaying signal. To prevent the eavesdropper from decoding this signal, a destination transmits a jamming noise while a source transmits the data signal to the relay. At the same time, the relay can harvest energy from both the source signal and the jamming noise, and use this harvested energy to forward the received signal to the destination. In such a wireless-powered relay system with cooperative jamming, we propose two adaptive relaying schemes based on power splitting and time switching techniques. In the proposed power splitting-based relaying (PSR) and time switching-based relaying (TSR) schemes, the relay controls the power splitting ratio (ρ) and time switching ratio (α), respectively, in order to achieve a balance between signal processing and energy harvesting. We find analytically the optimal values of ρ and α in each scheme to maximize the secrecy capacity under the assumption of high signal-to-noise ratio. Interestingly, although the eavesdropper’s channel state information (CSI) is used in the derivation of the optimal control parameters (ρ and α), they are shown not to be affected by the eavesdropper’s CSI in a high SNR regime. This implies that the proposed schemes can be effective even for practical environments where there is no eavesdropper’s CSI. Furthermore, simulation results show that they well coincide with the exact solutions in practical environments even though the closed-form solutions are obtained with a high SNR assumption. Moreover, the comparisons of PSR and TSR in various scenarios show that the two relaying schemes have complementary performances depending on the network conditions. Specifically, PSR achieves greater secrecy capacity than TSR when the channel condition is unfavourable to the eavesdropper for wiretapping.

    @article{lee-hong-2018-iotj,
      author = {Kisong Lee and Jun-Pyo Hong and Hyun-Ho Choi and Marco Levorato},
      title = {Adaptive Wireless-Powered Relaying Schemes With Cooperative Jamming for Two-Hop Secure Communication},
      journal = {IEEE Internet of Things Journal},
      volume = {5},
      number = {4},
      pages = {2793--2803},
      month = aug,
      year = {2018},
      doi = {10.1109/jiot.2018.2830880},
    }
  • Zoheb Shaikh
    Sabur Baidya
    Marco Levorato
    Z. Shaikh, S. Baidya, and M. Levorato, Robust Multi-Path Communications for UAVs in the Urban IoT, in Proceedings of the Workshop on Unmanned Autonomous Systems (CPC-UAV), Hong Kong, Jun. 2018, in conjunction with IEEE International Conference on Sensing, Communication and Networking (SECON). Release

    Unmanned Aerial Vehicle (UAV) systems are being increasingly used in a broad range of scenarios and applications. However, their deployment in urban areas poses important technical challenges. One of the most prominent concerns is the robustness of communications between the ground stations and the UAVs in a highly dynamic and crowded spectrum. Indeed, competing data streams may create local or temporary congestion impairing the ground stations to control the UAVs. The main contribution of this paper is a robust multi-path communication framework for UAV systems. The framework continuously probes the performance of multiple wireless multi-hop paths from the ground stations to each UAV, and dynamically selects the path providing the best performance to support timely control. Numerical results, based on a real-world implementation and extensive field experimentation, demonstrate the ability of the proposed framework to provide robust control against exogenous interference and network congestion.

    @inproceedings{shaikh-baidya-2018-cpcuav,
      author = {Zoheb Shaikh and Sabur Baidya and Marco Levorato},
      title = {Robust Multi-Path Communications for {UAVs} in the {Urban} {IoT}},
      booktitle = {Proceedings of the Workshop on Unmanned Autonomous Systems (CPC-UAV)},
      note = {in conjunction with IEEE International Conference on Sensing, Communication and Networking (SECON)},
      address = {Hong Kong},
      month = jun,
      year = {2018},
      doi = {10.1109/seconw.2018.8396356},
    }
  • Sanaz Rahimi Moosavi
    Ethiopia Nigussie
    Marco Levorato
    Seppo Virtanen
    Jouni Isoaho
    S. Rahimi Moosavi, E. Nigussie, M. Levorato, S. Virtanen, and J. Isoaho, Performance Analysis of End-to-End Security Schemes in Healthcare IoT, Procedia Computer Science, vol. 130, pp. 432 – 439, May 2018, Proceedings of the International Conference on Ambient Systems, Networks and Technologies (ANT). Release

    In this paper, we analyze the performance of the state-of-the-art end-to-end security schemes in healthcare Internet of Things (IoT) systems. We identify that the essential requirements of robust security solutions for healthcare IoT systems comprise of (i) low-latency secure key generation approach using patients’ Electrocardiogram (ECG) signals, (ii) secure and efficient authentication and authorization for healthcare IoT devices based on the certificate-based datagram Transport Layer Security (DTLS), and (iii) robust and secure mobility-enabled end-to-end communication based on DTLS session resumption. The performance of the state-of-the-art security solutions including our end-to-end security scheme is tested by developing a prototype healthcare IoT system. The prototype is built of a Pandaboard, a TI SmartRF06 board and WiSMotes. The Pandaboard along with the CC2538 module acts as a smart gateway and the WisMotes act as medical sensor nodes. Based on the analysis, we found out that our solution has the most extensive set of performance features in comparison to related approaches found in the literature. The performance evaluation results show that compared to the existing approaches, the cryptographic key generation approach proposed in our end-to-end security scheme is on average 1.8 times faster than existing key generation approaches while being more energy-efficient. In addition, the scheme reduces the communication overhead by 26% and the communication latency between smart gateways and end users by 16%. Our scheme is also approximately 97% faster than certificate based and 10% faster that symmetric key-based DTLS. Certificate based DTLS requires about 2.9 times more ROM and 2.2 times more RAM resources. On the other hand, the ROM and RAM requirements of our scheme are almost as low as in symmetric key-based DTLS.

    @article{moosavi-nigussie-2018-ant,
      author = {Sanaz {Rahimi Moosavi} and Ethiopia Nigussie and Marco Levorato and Seppo Virtanen and Jouni Isoaho},
      title = {Performance Analysis of End-to-End Security Schemes in Healthcare {IoT}},
      journal = {Procedia Computer Science},
      volume = {130},
      pages = {432--439},
      note = {Proceedings of the International Conference on Ambient Systems, Networks and Technologies (ANT)},
      publisher = {Elsevier},
      month = may,
      year = {2018},
      doi = {10.1016/j.procs.2018.04.064},
    }
  • Sabur Baidya
    Yan Chen
    Marco Levorato
    S. Baidya, Y. Chen, and M. Levorato, eBPF-Based Content and Computation-Aware Communication for Real-Time Edge Computing, in Proceedings of the IEEE International Conference on Computer Communications (INFOCOM) Workshops, Honolulu, Hawaii, Apr. 2018. Release

    By placing computation resources within a one-hop wireless topology, the recent edge computing paradigm is a key enabler of real-time Internet of Things (IoT) applications. In the context of IoT scenarios where the same information from a sensor is used by multiple applications at different locations, the data stream needs to be replicated. However, the transportation of parallel streams might not be feasible due to limitations in the capacity of the network transporting the data. To address this issue, a content and computation-aware communication control framework is proposed based on the Software Defined Network (SDN) paradigm. The framework supports multi-streaming using the extended Berkeley Packet Filter (eBPF), where the traffic flow and packet replication for each specific computation process is controlled by a program running inside an in-kernel Virtual Machine (VM). The proposed framework is instantiated to address a case-study scenario where video streams from multiple cameras are transmitted to the edge processor for real-time analysis. Numerical results demonstrate the advantage of the proposed framework in terms of programmability, network bandwidth and system resource savings.

    @inproceedings{baidya-chen-2018-infocom,
      author = {Sabur Baidya and Yan Chen and Marco Levorato},
      title = {{eBPF}-Based Content and Computation-Aware Communication for Real-Time Edge Computing},
      booktitle = {Proceedings of the IEEE International Conference on Computer Communications (INFOCOM) Workshops},
      address = {Honolulu, Hawaii},
      month = apr,
      year = {2018},
      doi = {10.1109/infcomw.2018.8407006},
    }
  • Aakanksha Chowdhery
    Marco Levorato
    Igor Burago
    Sabur Baidya
    Amir M. Rahmani
    Pasi Liljeberg
    Jürgo-Sören Preden
    Axel Jantsch
    A. Chowdhery, M. Levorato, I. Burago, and S. Baidya, Urban IoT Edge Analytics, in Fog Computing in the Internet of Things, A. M. Rahmani, P. Liljeberg, J.-S. Preden, and A. Jantsch, Eds. Springer, 2018, ch. 6, pp. 101 – 120. Release
    @incollection{chowdhery-levorato-2018-fogiot,
      author = {Aakanksha Chowdhery and Marco Levorato and Igor Burago and Sabur Baidya},
      title = {Urban {IoT} Edge Analytics},
      editor = {Amir M. Rahmani and Pasi Liljeberg and J{\"u}rgo-S{\"o}ren Preden and Axel Jantsch},
      booktitle = {Fog Computing in the Internet of Things},
      chapter = {6},
      pages = {101--120},
      publisher = {Springer},
      year = {2018},
      doi = {10.1007/978-3-319-57639-8_6},
    }

2017

  • Igor Burago
    Davide Callegaro
    Marco Levorato
    Sameer Singh
    I. Burago, D. Callegaro, M. Levorato, and S. Singh, Intelligent Data Filtering in Constrained IoT Systems, in Proceedings of the Asilomar Conference on Signals, Systems, and Computers (ACSSC), Pacific Groove, California, Oct. – Nov. 2017. Release

    The expansion of complex autonomous sensing and control mechanisms in the Internet-of-Things systems clashes with constraints on computation and wireless communication resources. In this paper, we propose a framework to address this conflict for applications in which resolution using a centralized architecture with a general-purpose compression of observations is not appropriate. Three approaches for distributing observation detection workload between sensing and processing devices are considered for sensor systems within wireless islands. Each of the approaches is formulated for the shared configuration of a sensor-edge system, in which the network structure, observation monitoring problem, and machine learning-based detector implementing it are not modified. For every approach, a high-level strategy for realization of the detector for different assumptions on the relation between its complexity and the system’s constraints is considered. In each case, the potential for the constraints’ satisfaction is shown to exist and be exploitable via division, approximation, and delegation of the detector’s workload to the sensing devices off the edge processor. We present examples of applications that benefit from the proposed approaches.

    @inproceedings{burago-callegaro-2017-acssc,
      author = {Igor Burago and Davide Callegaro and Marco Levorato and Sameer Singh},
      title = {Intelligent Data Filtering in Constrained {IoT} Systems},
      booktitle = {Proceedings of the Asilomar Conference on Signals, Systems, and Computers (ACSSC)},
      address = {Pacific Groove, California},
      month = oct # {--} # nov,
      year = {2017},
      doi = {10.1109/acssc.2017.8335485},
    }
  • Korosh Vatanparvar
    Sina Faezi
    Igor Burago
    Marco Levorato
    Mohammad Abdullah Al Faruque
    K. Vatanparvar, S. Faezi, I. Burago, M. Levorato, and M. A. Al Faruque, Driving Behavior Modeling and Estimation for Battery Optimization in Electric Vehicles: Work-in-Progress, in Proceedings of the IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis Companion (CODES), Seoul, Republic of Korea, Oct. 2017. Release

    Battery and energy management methodologies such as automotive climate controls have been proposed to address the design challenges of driving range and battery lifetime in Electric Vehicles (EV). However, driving behavior estimation is a major factor neglected in these methodologies. In this paper, we propose a novel context-aware methodology for estimating the driving behavior in terms of future vehicle speeds that will be integrated into the EV battery optimization. We implement a driving behavior model using a variation of Artificial Neural Networks (ANN) called Nonlinear AutoRegressive model with eXogenous inputs (NARX). We train our novel context-aware NARX model based on historical behavior of real drivers, their recent driving reactions, and the route average speed retrieved from Google Maps in order to enable driver-specific and self-adaptive driving behavior modeling and long-term estimation. Our methodology shows only 12% error for up to 30-second speed prediction which is improved by 27% compared to the state-of-the-art. Hence, it can achieve up to 82% of the maximum energy saving and battery lifetime improvement possible by the ideal methodology where the future vehicle speed is known.

    @inproceedings{vatanparvar-faezi-2017-codes,
      author = {Korosh Vatanparvar and Sina Faezi and Igor Burago and Marco Levorato and Mohammad Abdullah {Al~Faruque}},
      title = {Driving Behavior Modeling and Estimation for Battery Optimization in Electric Vehicles: Work-in-Progress},
      booktitle = {Proceedings of the IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis Companion (CODES)},
      address = {Seoul, Republic of Korea},
      month = oct,
      year = {2017},
      doi = {10.1145/3125502.3125542},
    }
  • Sanaz Rahimi Moosavi
    Ethiopia Nigussie
    Marco Levorato
    Seppo Virtanen
    Jouni Isoaho
    S. Rahimi Moosavi, E. Nigussie, M. Levorato, S. Virtanen, and J. Isoaho, Low-Latency Approach for Secure ECG Feature Based Cryptographic Key Generation, IEEE Access, vol. 6, pp. 428 – 442, Oct. 2017. Release

    We propose a low-latency approach for generating secure electrocardiogram (ECG) feature-based cryptographic keys. This is done by taking advantage of the uniqueness and randomness properties of ECG’s main features. This approach achieves a low-latency since the key generation relies on four reference-free ECG’s main features that can be acquired in short time. We call the approach several ECG features (SEF)-based cryptographic key generation. SEF consists of: 1) detecting the arrival time of ECG’s fiducial points using Daubechies wavelet transform to compute ECG’s main features accordingly; 2) using a dynamic technique to specify the optimum number of bits that can be extracted from each main ECG feature, comprising of PR, RR, PP, QT, and ST intervals; 3) generating cryptographic keys by exploiting the above-mentioned ECG features; and 4) consolidating and strengthening the SEF approach with cryptographically secure pseudo-random number generators. Fibonacci linear feedback shift register and advanced encryption standard algorithms are implemented as the pseudo-random number generator to enhance the security level of the generated cryptographic keys. Our approach is applied to 239 subjects’ ECG signals comprising of normal sinus rhythm, arrhythmia, atrial fibrillation, and myocardial infraction. The security analyses of the proposed approach are carried out in terms of distinctiveness, test of randomness, temporal variance, and using National Institute of Standards and Technology benchmark. The analyses reveal that the normal ECG rhythms have slightly better randomness compared with the abnormal ones. The analyses also show that the strengthened SEF key generation approach provides a higher security level in comparison to existing approaches that rely only on singleton ECG features. For the normal ECG rhythms, the SEF approach has in average the entropy of about 0.98 while cryptographic keys which are generated utilizing the strengthened SEF approach offer the entropy of ∼1. The execution time required to generate the cryptographic keys on different processors is also examined. The results reveal that our SEF approach is in average 1.8 times faster than existing key generation approaches which only utilize the inter pulse interval feature of ECG.

    @article{moosavi-nigussie-2017-access,
      author = {Sanaz {Rahimi Moosavi} and Ethiopia Nigussie and Marco Levorato and Seppo Virtanen and Jouni Isoaho},
      title = {Low-Latency Approach for Secure {ECG} Feature Based Cryptographic Key Generation},
      journal = {IEEE Access},
      volume = {6},
      pages = {428--442},
      month = oct,
      year = {2017},
      doi = {10.1109/access.2017.2766523},
    }
  • Iman Azimi
    Arman Anzanpour
    Amir M. Rahmani
    Tapio Pahikkala
    Marco Levorato
    Pasi Liljeberg
    Nikil Dutt
    I. Azimi, A. Anzanpour, et al.A. M. Rahmani, T. Pahikkala, M. Levorato, P. Liljeberg, and N. Dutt, HiCH: Hierarchical Fog-Assisted Computing Architecture for Healthcare IoT, ACM Transactions on Embedded Computing Systems, vol. 16, no. 5s, article no. 174, pp. 174:1 – 174:20, Sep. 2017. Release
    @article{azimi-anzanpour-2017-tecs,
      author = {Iman Azimi and Arman Anzanpour and Amir M. Rahmani and Tapio Pahikkala and Marco Levorato and Pasi Liljeberg and Nikil Dutt},
      title = {{HiCH}: Hierarchical Fog-Assisted Computing Architecture for Healthcare {IoT}},
      journal = {ACM Transactions on Embedded Computing Systems},
      volume = {16},
      number = {5s},
      pages = {174:1--174:20},
      month = sep,
      year = {2017},
      articleno = {174},
      doi = {10.1145/3126501},
    }
  • Nadia Ahmed
    Marco Levorato
    Guann-Pyng Li
    N. Ahmed, M. Levorato, and G.-P. Li, Residential Consumer-Centric Demand Side Management, IEEE Transactions on Smart Grid, vol. 9, no. 5, pp. 4513 – 4524, Sep. 2017. Release

    Energy management systems (EMS) are mainly price driven with minimal consumer interaction. To improve the effectiveness of EMS in the context of demand response, an alternative EMS control framework driven by resident behavior patterns is developed. Using hidden Markov modeling techniques, the EMS detects consumer behavior from real-time aggregate consumption and a pre-built dictionary of reference models. These models capture variations in consumer habits as a function of daily living activity sequence. Following a training period, the system identifies the best fit model which is used to estimate the current state of the resident. When a request to activate a time-shiftable appliance is made, the control agent compares grid signals, user convenience constraints, and the current consumer state estimate to predict the likelihood that the future aggregate load exceeds a consumption threshold during the operating cycle of the requested device. Based on the outcome, the control agent initiates or defers the activation request. Using three consumer reference models, a case study assessing EMS performance with respect to model detection, state estimation, and control as a function of consumer comfort and grid-informed consumption constraints is presented. A tradeoff analysis between comfort, consumption threshold, and appliance activation delay is demonstrated.

    @article{ahmed-levorato-2017-tsg,
      author = {Nadia Ahmed and Marco Levorato and Guann-Pyng Li},
      title = {Residential Consumer-Centric Demand Side Management},
      journal = {IEEE Transactions on Smart Grid},
      volume = {9},
      number = {5},
      pages = {4513--4524},
      month = sep,
      year = {2017},
      doi = {10.1109/tsg.2017.2661991},
    }
  • Igor Burago
    Marco Levorato
    Aakanksha Chowdhery
    I. Burago, M. Levorato, and A. Chowdhery, Bandwidth-Aware Data Filtering in Edge-Assisted Wireless Sensor Systems, in Proceedings of the IEEE International Conference on Sensing, Communication and Networking (SECON), San Diego, California, Jun. 2017. Release

    By placing processing-capable devices at the edge of local wireless access networks, Edge Computing architectures have been recently proposed to connect mobile devices to computational power through a one-hop low-latency wireless link. In this paper, we propose a new design where edge assistance is used to control local data filtering at the mobile devices in bandwidth and energy constrained systems. We focus on real-time monitoring applications, where the video input from mobile devices is processed to centrally detect and recognize objects. The edge processor controls the activation and deactivation of local classifiers implemented by the mobile devices to remove useless portions of video frames. The objective is to adapt the video stream to time-varying bandwidth constraints, while minimizing the additional energy consumption introduced by local processing. To this end, an optimization problem is formulated for a loss function embodying the balance between the risk of violating the available bandwidth and the cost of overly-conservative data filtering. The edge assists the local decision by extracting parameters of the video, such as density of objects of interest in a frame, which influence the output of the sensor. Numerical results, obtained by performing a measurement campaign based on a real implementation, illustrate the tension between energy and bandwidth use for a Haar feature-based cascade classifier.

    @inproceedings{burago-levorato-2017-secon,
      author = {Igor Burago and Marco Levorato and Aakanksha Chowdhery},
      title = {Bandwidth-Aware Data Filtering in Edge-Assisted Wireless Sensor Systems},
      booktitle = {Proceedings of the IEEE International Conference on Sensing, Communication and Networking (SECON)},
      address = {San Diego, California},
      month = jun,
      year = {2017},
      doi = {10.1109/sahcn.2017.7964938},
    }
  • Nicolò Michelusi
    Marco Levorato
    N. Michelusi and M. Levorato, Energy-Based Adaptive Multiple Access in LPWAN IoT Systems With Energy Harvesting, in Proceedings of the IEEE International Symposium on Information Theory (ISIT), Aachen, Germany, Jun. 2017. Release
    @inproceedings{michelusi-levorato-2017-isit,
      author = {Nicol{\`o} Michelusi and Marco Levorato},
      title = {Energy-Based Adaptive Multiple Access in {LPWAN} {IoT} Systems With Energy Harvesting},
      booktitle = {Proceedings of the IEEE International Symposium on Information Theory (ISIT)},
      address = {Aachen, Germany},
      month = jun,
      year = {2017},
      doi = {10.1109/isit.2017.8006701},
    }
  • Sabur Baidya
    Marco Levorato
    S. Baidya and M. Levorato, Edge-Assisted Content and Computation-Driven Dynamic Network Selection for Real-Time Services in Urban IoT, in Proceedings of the IEEE International Conference on Computer Communications (INFOCOM) Workshops, Atlanta, Georgia, May 2017. Release

    Supporting city-wide exchange of information in Urban Internet of Things (IoT) systems using existing communication infrastructures is extremely challenging especially when traditional services operate in the same network resource. Additionally, the most advanced Urban IoT services focus on real-time data processing, which shifts the perspective and goal of the network when transporting data. In this paper, the notion of Quality of Computing (QoC) is introduced to capture the level of support the communication infrastructure provides to this family of computation applications. In this context, we propose a dynamic network selection mechanism based on Software Defined Networks (SDN) designed to provide QoC in Urban IoT scenarios where the heterogeneous network resources are shared. The proposed mechanism dynamically assigns portions of data from IoT streams over licensed and unlicensed bands to guarantee QoC while minimizing cost of operations and licensed band occupation. Instrumental to our technique is the recently proposed edge-computing architecture, where computational resources placed at the edge of wireless access networks enable the interconnection of network management to processing. We consider a real-time monitoring scenario, where sensors transmit a video stream which is processed to identify and classify objects. The supporting wireless infrastructure consists of WiFi that operates in unlicensed frequency bands and cellular communication technology, Long Term Evolution (LTE) operating in licensed bands. We demonstrate the performance by means of real-world experiments on a testbed with WiFi and LTE networks built with hostapd and OpenAirInterface.

    @inproceedings{baidya-levorato-2017-infocom,
      author = {Sabur Baidya and Marco Levorato},
      title = {Edge-Assisted Content and Computation-Driven Dynamic Network Selection for Real-Time Services in Urban {IoT}},
      booktitle = {Proceedings of the IEEE International Conference on Computer Communications (INFOCOM) Workshops},
      address = {Atlanta, Georgia},
      month = may,
      year = {2017},
      doi = {10.1109/infcomw.2017.8116478},
    }
  • Marco Levorato
    M. Levorato, Cognitive Networking With Dynamic Traffic Classification and QoS Constraints, in Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC), San Francisco, California, Mar. 2017. Release
    @inproceedings{levorato-2017-wcnc,
      author = {Marco Levorato},
      title = {Cognitive Networking With Dynamic Traffic Classification and {QoS} Constraints},
      booktitle = {Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC)},
      address = {San Francisco, California},
      month = mar,
      year = {2017},
      doi = {10.1109/wcnc.2017.7925717},
    }
  • Igor Burago
    Marco Levorato
    Sameer Singh
    I. Burago, M. Levorato, and S. Singh, Semantic Compression for Edge-Assisted Systems, in Proceedings of the Information Theory and Applications Workshop (ITA), San Diego, California, Feb. 2017. Release

    A novel semantic approach to data selection and compression is presented for the dynamic adaptation of IoT data processing and transmission within “wireless islands”, where a set of sensing devices (sensors) are interconnected through one-hop wireless links to a computational resource via a local access point. The core of the proposed technique is a cooperative framework where local classifiers at the mobile nodes are dynamically crafted and updated based on the current state of the observed system, the global processing objective and the characteristics of the sensors and data streams. The edge processor plays a key role by establishing a link between content and operations within the distributed system. The local classifiers are designed to filter the data streams and provide only the needed information to the global classifier at the edge processor, thus minimizing bandwidth usage. However, the better the accuracy of these local classifiers, the larger the energy necessary to run them at the individual sensors. A formulation of the optimization problem for the dynamic construction of the classifiers under bandwidth and energy constraints is proposed and demonstrated on a synthetic example.

    @inproceedings{burago-levorato-2017-ita,
      author = {Igor Burago and Marco Levorato and Sameer Singh},
      title = {Semantic Compression for Edge-Assisted Systems},
      booktitle = {Proceedings of the Information Theory and Applications Workshop (ITA)},
      address = {San Diego, California},
      month = feb,
      year = {2017},
      doi = {10.1109/ita.2017.8023457},
    }
  • Sabur Baidya
    Marco Levorato
    S. Baidya and M. Levorato, Content-Based Interference Management for Video Transmission in D2D Communications Underlaying LTE, in Proceedings of the IEEE International Conference on Computing, Networking and Communications (ICNC), Silicon Valley, California, Jan. 2017, pp. 144 – 149. Release

    A novel interference management approach is proposed for modern communication scenarios, where multiple applications and networks coexist on the same channel resource. The leading principle behind the proposed approach is that the interference level should be adapted to the content being transmitted by the data links to maximize the amount of delivered information. A network setting is considered where Device-to-Device (D2D) communications underlay a Long Term Evolution (LTE) link uploading video content to the network infrastructure. For this scenario, an optimization problem is formulated aiming at the maximization of the D2D link’s throughput under a constraint on the Peak Signal-to-Noise-Ratio of the video data stream. The resulting optimal policy focuses interference on specific packets within the video stream, and significantly increases the throughput achieved by the D2D link compared to an undifferentiated interference strategy. The optimal strategy is applied to a real-world video streaming application to further demonstrate the performance gain.

    @inproceedings{baidya-levorato-2017-icnc,
      author = {Sabur Baidya and Marco Levorato},
      title = {Content-Based Interference Management for Video Transmission in {D2D} Communications Underlaying {LTE}},
      booktitle = {Proceedings of the IEEE International Conference on Computing, Networking and Communications (ICNC)},
      pages = {144--149},
      address = {Silicon Valley, California},
      month = jan,
      year = {2017},
      doi = {10.1109/iccnc.2017.7876117},
    }

2016

  • Sabur Baidya
    Marco Levorato
    S. Baidya and M. Levorato, Content-Based Cognitive Interference Control for City Monitoring Applications in the Urban IoT, in Proceedings of the IEEE Global Communications Conference (GLOBECOM), Washington, DC, Dec. 2016. Release

    In the Urban Internet of Things (IoT), devices and systems are interconnected at the city scale to provide innovative services to the citizens. However, the traffic generated by the sensing and processing systems may overload local access networks. A coexistence problem arises where concurrent applications mutually interfere and compete for available resources. This effect is further aggravated by the multiple scales involved and heterogeneity of the networks supporting the urban IoT. One of the main contributions of this paper is the introduction of the notion of content-oriented cognitive interference control in heterogeneous local access networks supporting computing and data processing in the urban IoT. A network scenario where multiple communication technologies, such as Device-to-Device and Long Term Evolution (LTE), is considered. The focus of the present paper is on city monitoring applications, where a video data stream generated by a camera system is remotely processed to detect objects. The cognitive network paradigm is extended to dynamically shape the interference pattern generated by concurrent data streams and induce a packet loss trajectory compatible with video processing algorithms. Numerical results show that the proposed cognitive transmission strategy enables a significant throughput increase of interfering applications for a target accuracy of the monitoring application.

    @inproceedings{baidya-levorato-2016-globecom,
      author = {Sabur Baidya and Marco Levorato},
      title = {Content-Based Cognitive Interference Control for City Monitoring Applications in the Urban {IoT}},
      booktitle = {Proceedings of the IEEE Global Communications Conference (GLOBECOM)},
      address = {Washington, DC},
      month = dec,
      year = {2016},
      doi = {10.1109/glocom.2016.7841693},
    }
  • Marco Levorato
    Pradeep Chathuranga Weeraddana
    Carlo Fischione
    M. Levorato, P. C. Weeraddana, and C. Fischione, Distributed Optimization of Channel Access Strategies in Reactive Cognitive Networks, IEEE Transactions on Communications, vol. 64, no. 10, pp. 4121 – 4133, Oct. 2016. Release
    @article{levorato-weeraddana-2016-tcom,
      author = {Marco Levorato and Pradeep Chathuranga Weeraddana and Carlo Fischione},
      title = {Distributed Optimization of Channel Access Strategies in Reactive Cognitive Networks},
      journal = {IEEE Transactions on Communications},
      volume = {64},
      number = {10},
      pages = {4121--4133},
      month = oct,
      year = {2016},
      doi = {10.1109/tcomm.2016.2602207},
    }
  • Roberto Valentini
    Marco Levorato
    R. Valentini and M. Levorato, Optimal Aging-Aware Channel Access Control for Wireless Networks With Energy Harvesting, in Proceedings of the IEEE International Symposium on Information Theory (ISIT), Barcelona, Spain, Jul. 2016. Release

    Energy harvesting is arising as a key technology in wireless systems, allowing continuous and prolonged operations. However, the bursty nature of the energy arrival process associated with renewable sources and the energy usage pattern caused by wireless protocols may cause considerable stress to the battery and eventually reduce its lifetime. In fact, deep charging and discharging cycles degrade the battery State of Health, that is, the maximum amount of energy that can be stored. In this paper, a framework for the optimization of wireless nodes’ transmission strategy is presented, where battery aging rate is included as a constraint. The proposed framework is based on Markov Decision Process theory, where the embedded stochastic process models energy arrival and storage, and channel fading, as well as the control variables. Numerical results unveil the tension between packet delivery rate and battery degradation.

    @inproceedings{valentini-levorato-2016-isit,
      author = {Roberto Valentini and Marco Levorato},
      title = {Optimal Aging-Aware Channel Access Control for Wireless Networks With Energy Harvesting},
      booktitle = {Proceedings of the IEEE International Symposium on Information Theory (ISIT)},
      address = {Barcelona, Spain},
      month = jul,
      year = {2016},
      doi = {10.1109/isit.2016.7541800},
    }
  • Roberto Valentini
    Marco Levorato
    Fortunato Santucci
    R. Valentini, M. Levorato, and F. Santucci, Aging Aware Random Channel Access for Battery-Powered Wireless Networks, IEEE Wireless Communications Letters, vol. 5, no. 2, pp. 176 – 179, Apr. 2016. Release

    Energy harvesting is becoming a key technology in mobile wireless networks, and especially sensor systems. The bursty nature of energy arrival generated by renewable resources may apply considerable stress to the battery, and degrade its state of health (SoH) by generating deep charging and discharging cycles. In this letter, a novel random channel access scheme is proposed that tunes transmission parameters to reduce SoH degradation while preserving the network performance.

    @article{valentini-levorato-2016-wcl,
      author = {Roberto Valentini and Marco Levorato and Fortunato Santucci},
      title = {Aging Aware Random Channel Access for Battery-Powered Wireless Networks},
      journal = {IEEE Wireless Communications Letters},
      volume = {5},
      number = {2},
      pages = {176--179},
      month = apr,
      year = {2016},
      doi = {10.1109/lwc.2016.2515079},
    }

2015

  • Nga Dang
    Roberto Valentini
    Eli Bozorgzadeh
    Marco Levorato
    Nalini Venkatasubramanian
    N. Dang, R. Valentini, E. Bozorgzadeh, M. Levorato, and N. Venkatasubramanian, A Unified Stochastic Model for Energy Management in Solar-Powered Embedded Systems, in Proceedings of the IEEE/ACM International Conference on Computer-Aided Design (ICCAD), Austin, Texas, Nov. 2015. Release

    Energy harvesting from environments such as solar energy are promising solutions to tackle energy sustainability in embedded systems. However, uncertainties in energy availability, non-ideal characteristics of harvesting circuits, energy storage (battery or supercapacitor), and application demand dynamics add more complexity in the system. We present a unified model based on discrete-time Finite State Markov Chain to capture the dynamicity and variations in both the energy supply from solar irradiance and the energy demand from the application. In this paper, we exploit the temporal and spatial characteristics of solar energy and propose a deterministic profile with stochastic process to reflect the fluctuation due to unexpected weather condition. Optimal policy to maximize expected total QoS is derived from the presented model using a probabilistic dynamic programming approach. Compared to a state-of-the-art deterministic energy management framework, our proposed approach outperforms in term of QoS and energy sustainability (with less shutdown time) of the system.

    @inproceedings{dang-valentini-2015-iccad,
      author = {Nga Dang and Roberto Valentini and Eli Bozorgzadeh and Marco Levorato and Nalini Venkatasubramanian},
      title = {A Unified Stochastic Model for Energy Management in Solar-Powered Embedded Systems},
      booktitle = {Proceedings of the IEEE/ACM International Conference on Computer-Aided Design (ICCAD)},
      address = {Austin, Texas},
      month = nov,
      year = {2015},
      doi = {10.1109/iccad.2015.7372627},
    }
  • Roberto Valentini
    Nga Dang
    Marco Levorato
    Eli Bozorgzadeh
    R. Valentini, N. Dang, M. Levorato, and E. Bozorgzadeh, Modeling and Control Battery Aging in Energy Harvesting Systems, in Proceedings of the IEEE International Conference on Smart Grid Communications (SmartGridComm), Miami, Florida, Nov. 2015. Release

    Energy storage is a fundamental component for the development of sustainable and environment-aware technologies. One of the critical challenges that needs to be overcome is preserving the State of Health (SoH) in energy harvesting systems, where bursty arrival of energy and load may severely degrade the battery. Tools from Markov process and Dynamic Programming theory are becoming an increasingly popular choice to control dynamics of these systems due to their ability to seamlessly incorporate heterogeneous components and support a wide range of applications. Mapping aging rate measures to fit within the boundaries of these tools is non-trivial. In this paper, a framework for modeling and controlling the aging rate of batteries based on Markov process theory is presented. Numerical results illustrate the tradeoff between battery degradation and task completion delay enabled by the proposed framework.

    @inproceedings{valentini-dang-2015-smartgridcomm,
      author = {Roberto Valentini and Nga Dang and Marco Levorato and Eli Bozorgzadeh},
      title = {Modeling and Control Battery Aging in Energy Harvesting Systems},
      booktitle = {Proceedings of the IEEE International Conference on Smart Grid Communications (SmartGridComm)},
      address = {Miami, Florida},
      month = nov,
      year = {2015},
      doi = {10.1109/smartgridcomm.2015.7436352},
    }
  • Igor Burago
    Marco Levorato
    I. Burago and M. Levorato, Network Estimation in Cognition-Empowered Wireless Networks, IEEE Transactions on Cognitive Communications and Networking, vol. 1, no. 2, pp. 244 – 256, Jun. 2015. Release

    An approach to parametric identification of the transmission processes of the terminals in a wireless network is proposed, presenting a trade-off between accuracy of capturing the temporal dependencies in observations of transmission processes and the time complexity of the estimation procedure. The maximum likelihood estimator is built for an approximation of the true likelihood function for the observed network activity. A complex network where terminals store packets in a finite buffer and implement a backoff-based random channel access protocol is considered. Minimal information is available for observation to the cognitive terminals, in the form of energy readings mapped to the number of transmitting nodes in each time instant. The entanglement of the transmission processes induced by interference and the filtering effect of packet buffering make this task particularly difficult. It is shown how, based on the estimated parameters, the cognitive terminals, operating in the same channel resource, can predict the transmission trajectories of the other nodes and devise smart transmission strategies controlling the interference generated to the network.

    @article{burago-levorato-2015-tccn,
      author = {Igor Burago and Marco Levorato},
      title = {Network Estimation in Cognition-Empowered Wireless Networks},
      journal = {IEEE Transactions on Cognitive Communications and Networking},
      volume = {1},
      number = {2},
      pages = {244--256},
      month = jun,
      year = {2015},
      doi = {10.1109/tccn.2016.2517013},
    }
  • Roberto Valentini
    Marco Levorato
    Carlo Fischione
    R. Valentini, M. Levorato, and C. Fischione, Performance Analysis of IEEE 802.15.3c-Based mmW Wireless Networks, in Proceedings of the Conference on Information Sciences and Systems (CISS), Baltimore, Maryland, Mar. 2015. Release

    The IEEE 802.15.3c standard defines physical layer and Medium Access Control (MAC) specifications for millimeter-Wave Wireless Personal Area Networks. The MAC protocol implements a combination of random channel access and time division multiple access mechanisms to exploit the sectorization granted by the directional antennas. In this work, a novel two-level stochastic model is presented to capture the complex dynamics of channel access in this network environment. Different from prior work, the finite temporal horizon of the channel contention phase is accurately modeled, and the common assumption of saturated terminals is removed. Based on the proposed modeling framework, the allocation of time resource to each sector is optimized to improve the network performance.

    @inproceedings{valentini-levorato-2015-ciss,
      author = {Roberto Valentini and Marco Levorato and Carlo Fischione},
      title = {Performance Analysis of {IEEE} {802.15.3c}-Based {mmW} Wireless Networks},
      booktitle = {Proceedings of the Conference on Information Sciences and Systems (CISS)},
      address = {Baltimore, Maryland},
      month = mar,
      year = {2015},
      doi = {10.1109/ciss.2015.7086886},
    }
  • Marco Levorato
    Nalini Venkatasubramanian
    Nikil Dutt
    M. Levorato, N. Venkatasubramanian, and N. Dutt, Heat-Aware Transmission Strategies, in Proceedings of the Information Theory and Applications Workshop (ITA), San Diego, California, Feb. 2015. Release
    @inproceedings{levorato-venkatasubramanian-2015-ita,
      author = {Marco Levorato and Nalini Venkatasubramanian and Nikil Dutt},
      title = {Heat-Aware Transmission Strategies},
      booktitle = {Proceedings of the Information Theory and Applications Workshop (ITA)},
      address = {San Diego, California},
      month = feb,
      year = {2015},
      doi = {10.1109/ita.2015.7308981},
    }

2014

  • Daphney-Stavroula Zois
    Marco Levorato
    Urbashi Mitra
    D.-S. Zois, M. Levorato, and U. Mitra, Active Classification for POMDPs: A Kalman-Like State Estimator, IEEE Transactions on Signal Processing, vol. 62, no. 23, pp. 6209 – 6224, Dec. 2014. Release
    @article{zois-levorato-2014-tsp,
      author = {Daphney-Stavroula Zois and Marco Levorato and Urbashi Mitra},
      title = {Active Classification for {POMDPs}: A Kalman-Like State Estimator},
      journal = {IEEE Transactions on Signal Processing},
      volume = {62},
      number = {23},
      pages = {6209--6224},
      month = dec,
      year = {2014},
      doi = {10.1109/tsp.2014.2362098},
    }
  • Marco Levorato
    Pradeep Chathuranga Weeraddana
    Carlo Fischione
    M. Levorato, P. C. Weeraddana, and C. Fischione, Distributed Optimization of Transmission Strategies in Reactive Cognitive Networks, in Proceedings of the IEEE Global Communications Conference (GLOBECOM), Austin, Texas, Dec. 2014. Release
    @inproceedings{levorato-weeraddana-2014-globecom,
      author = {Marco Levorato and Pradeep Chathuranga Weeraddana and Carlo Fischione},
      title = {Distributed Optimization of Transmission Strategies in Reactive Cognitive Networks},
      booktitle = {Proceedings of the IEEE Global Communications Conference (GLOBECOM)},
      address = {Austin, Texas},
      month = dec,
      year = {2014},
      doi = {10.1109/glocom.2014.7036924},
    }
  • Federico Librino
    Marco Levorato
    Michele Zorzi
    F. Librino, M. Levorato, and M. Zorzi, An Algorithmic Solution for Computing Circle Intersection Areas and Its Applications to Wireless Communications, Wireless Communications and Mobile Computing, vol. 14, no. 18, pp. 1672 – 1690, Dec. 2014. Release
    @article{librino-levorato-2014-wcmc,
      author = {Federico Librino and Marco Levorato and Michele Zorzi},
      title = {An Algorithmic Solution for Computing Circle Intersection Areas and Its Applications to Wireless Communications},
      journal = {Wireless Communications and Mobile Computing},
      volume = {14},
      number = {18},
      pages = {1672--1690},
      publisher = {Wiley},
      month = dec,
      year = {2014},
      doi = {10.1002/wcm.2305},
    }
  • Marco Levorato
    Nadia Ahmed
    Yang Arthur Zhang
    M. Levorato, N. Ahmed, and Y. A. Zhang, Consumer In-The-Loop: Consumers as Part of Residential Smart Energy Systems, in Proceedings of the IEEE International Conference on Smart Grid Communications (SmartGridComm), Venice, Italy, Nov. 2014. Release

    A novel framework for residential smart energy systems is proposed. The model integrates the consumer behavior in the dynamics of the technological and environmental components of the system. The objective is to classify and optimize the whole system, which includes the dynamics of the consumer. The framework is based on Markov process, model detection and Hidden Markov Model Theory. The behavior of the consumer is classified from a sequence of available observations within a set of reference classes. The detected class is used as prior information to detect the state of the system and provide feedback to the consumer to reduce the probability that undesirable states occur within a time window.

    @inproceedings{levorato-ahmed-2014-smartgridcomm,
      author = {Marco Levorato and Nadia Ahmed and Yang Arthur Zhang},
      title = {Consumer In-The-Loop: Consumers as Part of Residential Smart Energy Systems},
      booktitle = {Proceedings of the IEEE International Conference on Smart Grid Communications (SmartGridComm)},
      address = {Venice, Italy},
      month = nov,
      year = {2014},
      doi = {10.1109/smartgridcomm.2014.7007739},
    }

2013

  • Marco Levorato
    Sunil Narang
    Urbashi Mitra
    Antonio Ortega
    M. Levorato, S. Narang, U. Mitra, and A. Ortega, Optimization of Wireless Networks via Graph Interpolation, in Proceedings of the IEEE Global Conference on Signal and Information Processing (GlobalSIP), Austin, Texas, Dec. 2013, invited paper. Release
    @inproceedings{levorato-narang-2013-globalsip,
      author = {Marco Levorato and Sunil Narang and Urbashi Mitra and Antonio Ortega},
      title = {Optimization of Wireless Networks via Graph Interpolation},
      booktitle = {Proceedings of the IEEE Global Conference on Signal and Information Processing (GlobalSIP)},
      note = {invited paper},
      address = {Austin, Texas},
      month = dec,
      year = {2013},
      doi = {10.1109/globalsip.2013.6736920},
    }
  • Nicolò Michelusi
    Petar Popovski
    Osvaldo Simeone
    Marco Levorato
    Michele Zorzi
    N. Michelusi, P. Popovski, O. Simeone, M. Levorato, and M. Zorzi, Cognitive Access Policies Under a Primary ARQ Process via Forward-Backward Interference Cancellation, IEEE Journal on Selected Areas in Communications, vol. 31, no. 11, pp. 2374 – 2386, Nov. 2013. Release
    @article{michelusi-popovski-2013-jsac,
      author = {Nicol{\`o} Michelusi and Petar Popovski and Osvaldo Simeone and Marco Levorato and Michele Zorzi},
      title = {Cognitive Access Policies Under a Primary {ARQ} Process via Forward-Backward Interference Cancellation},
      journal = {IEEE Journal on Selected Areas in Communications},
      volume = {31},
      number = {11},
      pages = {2374--2386},
      month = nov,
      year = {2013},
      doi = {10.1109/jsac.2013.131112},
    }
  • Marco Levorato
    Urbashi Mitra
    M. Levorato and U. Mitra, Cognitive Networks With Dynamic User Classification for Tactical Communications, in Proceedings of the Military Communications Conference (MILCOM), San Diego, California, Nov. 2013. Release
    @inproceedings{levorato-mitra-2013-milcom,
      author = {Marco Levorato and Urbashi Mitra},
      title = {Cognitive Networks With Dynamic User Classification for Tactical Communications},
      booktitle = {Proceedings of the Military Communications Conference (MILCOM)},
      address = {San Diego, California},
      month = nov,
      year = {2013},
      doi = {10.1109/milcom.2013.284},
    }
  • Daphney-Stavroula Zois
    Marco Levorato
    Urbashi Mitra
    D.-S. Zois, M. Levorato, and U. Mitra, Non-Linear Smoothers for Discrete-Time, Finite-State Markov Chains, in Proceedings of the IEEE International Symposium on Information Theory (ISIT), Istanbul, Turkey, Jul. 2013. Release
    @inproceedings{zois-levorato-2013-isit,
      author = {Daphney-Stavroula Zois and Marco Levorato and Urbashi Mitra},
      title = {Non-Linear Smoothers for Discrete-Time, Finite-State Markov Chains},
      booktitle = {Proceedings of the IEEE International Symposium on Information Theory (ISIT)},
      address = {Istanbul, Turkey},
      month = jul,
      year = {2013},
      doi = {10.1109/isit.2013.6620596},
    }
  • Daphney-Stavroula Zois
    Marco Levorato
    Urbashi Mitra
    D.-S. Zois, M. Levorato, and U. Mitra, Kalman-Like State Tracking and Control in POMDPs With Applications to Body Sensing Networks, in Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Vancouver, Canada, May 2013. Release
    @inproceedings{zois-levorato-2013-icassp,
      author = {Daphney-Stavroula Zois and Marco Levorato and Urbashi Mitra},
      title = {Kalman-Like State Tracking and Control in {POMDPs} With Applications to Body Sensing Networks},
      booktitle = {Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
      address = {Vancouver, Canada},
      month = may,
      year = {2013},
      doi = {10.1109/icassp.2013.6638759},
    }
  • Daphney-Stavroula Zois
    Marco Levorato
    Urbashi Mitra
    D.-S. Zois, M. Levorato, and U. Mitra, Energy-Efficient, Heterogeneous Sensor Selection for Physical Activity Detection in Wireless Body Area Networks, IEEE Transactions on Signal Processing, vol. 61, no. 7, pp. 1581 – 1594, Apr. 2013. Release
    @article{zois-levorato-2013-tsp,
      author = {Daphney-Stavroula Zois and Marco Levorato and Urbashi Mitra},
      title = {Energy-Efficient, Heterogeneous Sensor Selection for Physical Activity Detection in Wireless Body Area Networks},
      journal = {IEEE Transactions on Signal Processing},
      volume = {61},
      number = {7},
      pages = {1581--1594},
      month = apr,
      year = {2013},
      doi = {10.1109/tsp.2012.2236320},
    }

2012

  • Marco Levorato
    Urbashi Mitra
    Andrea Goldsmith
    M. Levorato, U. Mitra, and A. Goldsmith, Structure-Based Learning in Wireless Networks via Sparse Approximation, EURASIP Journal on Wireless Communications and Networking, vol. 2012, no. 1, article no. 278, Dec. 2012. Release
    @article{levorato-mitra-2012-jwcn,
      author = {Marco Levorato and Urbashi Mitra and Andrea Goldsmith},
      title = {Structure-Based Learning in Wireless Networks via Sparse Approximation},
      journal = {EURASIP Journal on Wireless Communications and Networking},
      volume = {2012},
      number = {1},
      publisher = {Springer},
      month = dec,
      year = {2012},
      articleno = {278},
      doi = {10.1186/1687-1499-2012-278},
    }
  • Marco Levorato
    Urbashi Mitra
    M. Levorato and U. Mitra, Scale Invariance and Long-Range Dependence in Smart Energy Grids, in Proceedings of the Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Hollywood, California, Dec. 2012.
    @inproceedings{levorato-mitra-2012-apsipa,
      author = {Marco Levorato and Urbashi Mitra},
      title = {Scale Invariance and Long-Range Dependence in Smart Energy Grids},
      booktitle = {Proceedings of the Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)},
      address = {Hollywood, California},
      month = dec,
      year = {2012},
      url = {https://ieeexplore.ieee.org/abstract/document/6411979/},
    }
  • Marco Levorato
    Sunil Narang
    Urbashi Mitra
    Antonio Ortega
    M. Levorato, S. Narang, U. Mitra, and A. Ortega, Reduced Dimension Policy Iteration for Wireless Network Control via Multiscale Analysis, in Proceedings of the IEEE Global Communications Conference (GLOBECOM), Anaheim, California, Dec. 2012, best paper award. Release
    @inproceedings{levorato-narang-2012-globecom,
      author = {Marco Levorato and Sunil Narang and Urbashi Mitra and Antonio Ortega},
      title = {Reduced Dimension Policy Iteration for Wireless Network Control via Multiscale Analysis},
      booktitle = {Proceedings of the IEEE Global Communications Conference (GLOBECOM)},
      note = {best paper award},
      address = {Anaheim, California},
      month = dec,
      year = {2012},
      doi = {10.1109/glocom.2012.6503723},
    }
  • Andrea Munari
    Marco Levorato
    Michele Zorzi
    A. Munari, M. Levorato, and M. Zorzi, On the Impact of Carrier Sense Based Medium Access Control on Cooperative Schemes in Wireless Ad Hoc Networks, IEEE Transactions on Communications, vol. 60, no. 10, pp. 3032 – 3046, Oct. 2012. Release
    @article{munari-levorato-2012-tcom,
      author = {Andrea Munari and Marco Levorato and Michele Zorzi},
      title = {On the Impact of Carrier Sense Based Medium Access Control on Cooperative Schemes in Wireless Ad Hoc Networks},
      journal = {IEEE Transactions on Communications},
      volume = {60},
      number = {10},
      pages = {3032--3046},
      month = oct,
      year = {2012},
      doi = {10.1109/tcomm.2012.080312.100657},
    }
  • Apostol T. Gjika
    Marco Levorato
    Antonio Ortega
    Urbashi Mitra
    A. T. Gjika, M. Levorato, A. Ortega, and U. Mitra, Online Learning in Wireless Networks via Directed Graph Lifting Transform, in Proceedings of the Allerton Conference on Communication, Control and Computing, Monticello, Illinois, Oct. 2012, invited paper. Release
    @inproceedings{gjika-levorato-2012-allerton,
      author = {Apostol T. Gjika and Marco Levorato and Antonio Ortega and Urbashi Mitra},
      title = {Online Learning in Wireless Networks via Directed Graph Lifting Transform},
      booktitle = {Proceedings of the Allerton Conference on Communication, Control and Computing},
      note = {invited paper},
      address = {Monticello, Illinois},
      month = oct,
      year = {2012},
      doi = {10.1109/allerton.2012.6483328},
    }
  • Marco Levorato
    Sina Firouzabadi
    Andrea Goldsmith
    M. Levorato, S. Firouzabadi, and A. Goldsmith, A Learning Framework for Cognitive Interference Networks With Partial and Noisy Observations, IEEE Transactions on Wireless Communications, vol. 11, no. 9, pp. 3101 – 3111, Sep. 2012. Release
    @article{levorato-firouzabadi-2012-twc,
      author = {Marco Levorato and Sina Firouzabadi and Andrea Goldsmith},
      title = {A Learning Framework for Cognitive Interference Networks With Partial and Noisy Observations},
      journal = {IEEE Transactions on Wireless Communications},
      volume = {11},
      number = {9},
      pages = {3101--3111},
      month = sep,
      year = {2012},
      doi = {10.1109/twc.2012.062012.111342},
    }
  • Marco Levorato
    Urbashi Mitra
    M. Levorato and U. Mitra, Fast Anomaly Detection in Smart Grids via Sparse Approximation Theory, in Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), Stevens Institute of Technology, Hoboken, New Jersey, Jun. 2012, invited paper. Release
    @inproceedings{levorato-mitra-2012-sam,
      author = {Marco Levorato and Urbashi Mitra},
      title = {Fast Anomaly Detection in Smart Grids via Sparse Approximation Theory},
      booktitle = {Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)},
      note = {invited paper},
      address = {Stevens Institute of Technology, Hoboken, New Jersey},
      month = jun,
      year = {2012},
      doi = {10.1109/sam.2012.6250561},
    }
  • Daphney-Stavroula Zois
    Marco Levorato
    Urbashi Mitra
    D.-S. Zois, M. Levorato, and U. Mitra, Heterogeneous Time-Resource Allocation in Wireless Body Area Networks for Green, Maximum Likelihood Activity Detection, in Proceedings of the IEEE International Conference on Communications (ICC), Ottawa, Canada, Jun. 2012. Release
    @inproceedings{zois-levorato-2012-icc,
      author = {Daphney-Stavroula Zois and Marco Levorato and Urbashi Mitra},
      title = {Heterogeneous Time-Resource Allocation in Wireless Body Area Networks for Green, Maximum Likelihood Activity Detection},
      booktitle = {Proceedings of the IEEE International Conference on Communications (ICC)},
      address = {Ottawa, Canada},
      month = jun,
      year = {2012},
      doi = {10.1109/icc.2012.6364460},
    }
  • Marco Levorato
    Urbashi Mitra
    Michele Zorzi
    M. Levorato, U. Mitra, and M. Zorzi, Cognitive Interference Management in Retransmission-Based Wireless Networks, IEEE Transactions on Information Theory, vol. 58, no. 5, pp. 3023 – 3046, May 2012. Release
    @article{levorato-mitra-2012-tit,
      author = {Marco Levorato and Urbashi Mitra and Michele Zorzi},
      title = {Cognitive Interference Management in Retransmission-Based Wireless Networks},
      journal = {IEEE Transactions on Information Theory},
      volume = {58},
      number = {5},
      pages = {3023--3046},
      month = may,
      year = {2012},
      doi = {10.1109/tit.2012.2184691},
    }
  • Urbashi Mitra
    B. Adar Emken
    Sangwon Lee
    Ming Li
    Viktor Rozgic
    Gautam Thatte
    Harshvardhan Vathsangam
    Daphney-Stavroula Zois
    Murali Annavaram
    Shrikanth Narayanan
    Marco Levorato
    Donna Spruijt-Metz
    Gaurav Sukhatme
    U. Mitra, B. A. Emken, et al.S. Lee, M. Li, V. Rozgic, G. Thatte, H. Vathsangam, D.-S. Zois, M. Annavaram, S. Narayanan, M. Levorato, D. Spruijt-Metz, and G. Sukhatme, KNOWME: A Case Study in Wireless Body Area Sensor Network Design, IEEE Communications Magazine, vol. 50, no. 5, pp. 116 – 125, May 2012. Release
    @article{mitra-emken-2012-commag,
      author = {Urbashi Mitra and B. Adar Emken and Sangwon Lee and Ming Li and Viktor Rozgic and Gautam Thatte and Harshvardhan Vathsangam and Daphney-Stavroula Zois and Murali Annavaram and Shrikanth Narayanan and Marco Levorato and Donna Spruijt-Metz and Gaurav Sukhatme},
      title = {{KNOWME}: A Case Study in Wireless Body Area Sensor Network Design},
      journal = {IEEE Communications Magazine},
      volume = {50},
      number = {5},
      pages = {116--125},
      month = may,
      year = {2012},
      doi = {10.1109/mcom.2012.6194391},
    }
  • Daphney-Stavroula Zois
    Marco Levorato
    Urbashi Mitra
    D.-S. Zois, M. Levorato, and U. Mitra, A POMDP Framework for Heterogeneous Sensor Selection in Wireless Body Area Networks, in Proceedings of the IEEE International Conference on Computer Communications (INFOCOM), Orlando, Florida, Mar. 2012. Release
    @inproceedings{zois-levorato-2012-infocom,
      author = {Daphney-Stavroula Zois and Marco Levorato and Urbashi Mitra},
      title = {A {POMDP} Framework for Heterogeneous Sensor Selection in Wireless Body Area Networks},
      booktitle = {Proceedings of the IEEE International Conference on Computer Communications (INFOCOM)},
      address = {Orlando, Florida},
      month = mar,
      year = {2012},
      doi = {10.1109/infcom.2012.6195663},
    }

2011

  • Marco Levorato
    Sina Firouzabadi
    Andrea Goldsmith
    M. Levorato, S. Firouzabadi, and A. Goldsmith, Cognitive Interference Networks With Partial and Noisy Observations: A Learning Framework, in Proceedings of the IEEE Global Communications Conference (GLOBECOM), Houston, Texas, Dec. 2011. Release
    @inproceedings{levorato-firouzabadi-2011-globecom,
      author = {Marco Levorato and Sina Firouzabadi and Andrea Goldsmith},
      title = {Cognitive Interference Networks With Partial and Noisy Observations: A Learning Framework},
      booktitle = {Proceedings of the IEEE Global Communications Conference (GLOBECOM)},
      address = {Houston, Texas},
      month = dec,
      year = {2011},
      doi = {10.1109/glocom.2011.6134467},
    }
  • Marco Levorato
    Urbashi Mitra
    M. Levorato and U. Mitra, Optimal Allocation of Heterogeneous Smart Grid Traffic to Heterogeneous Networks, in Proceedings of the IEEE International Conference on Smart Grid Communications (SmartGridComm), Brussels, Belgium, Oct. 2011. Release
    @inproceedings{levorato-mitra-2011-smartgridcomm,
      author = {Marco Levorato and Urbashi Mitra},
      title = {Optimal Allocation of Heterogeneous Smart Grid Traffic to Heterogeneous Networks},
      booktitle = {Proceedings of the IEEE International Conference on Smart Grid Communications (SmartGridComm)},
      address = {Brussels, Belgium},
      month = oct,
      year = {2011},
      doi = {10.1109/smartgridcomm.2011.6102304},
    }
  • Marco Levorato
    Sina Firouzabadi
    Andrea Goldsmith
    M. Levorato, S. Firouzabadi, and A. Goldsmith, A Learning Framework for Cognitive Interference Networks With Partial and Noisy Observations, in Proceedings of the Allerton Conference on Communication, Control and Computing, Monticello, Illinois, Sep. 2011. Release
    @inproceedings{levorato-firouzabadi-2011-allerton,
      author = {Marco Levorato and Sina Firouzabadi and Andrea Goldsmith},
      title = {A Learning Framework for Cognitive Interference Networks With Partial and Noisy Observations},
      booktitle = {Proceedings of the Allerton Conference on Communication, Control and Computing},
      address = {Monticello, Illinois},
      month = sep,
      year = {2011},
      doi = {10.1109/twc.2012.062012.111342},
    }
  • Nicolò Michelusi
    Osvaldo Simeone
    Marco Levorato
    Petar Popovski
    Michele Zorzi
    N. Michelusi, O. Simeone, M. Levorato, P. Popovski, and M. Zorzi, Cognitive Transmissions Under a Primary ARQ Process via Backward Interference Cancellation, in Proceedings of the Allerton Conference on Communication, Control and Computing, Monticello, Illinois, Sep. 2011. Release
    @inproceedings{michelusi-simeone-2011-allerton,
      author = {Nicol{\`o} Michelusi and Osvaldo Simeone and Marco Levorato and Petar Popovski and Michele Zorzi},
      title = {Cognitive Transmissions Under a Primary {ARQ} Process via Backward Interference Cancellation},
      booktitle = {Proceedings of the Allerton Conference on Communication, Control and Computing},
      address = {Monticello, Illinois},
      month = sep,
      year = {2011},
      doi = {10.1109/allerton.2011.6120240},
    }
  • Marco Levorato
    Federico Librino
    Michele Zorzi
    M. Levorato, F. Librino, and M. Zorzi, Integrated Cooperative Opportunistic Packet Forwarding and Distributed Error Control in MIMO Ad Hoc Networks, IEEE Transactions on Communications, vol. 59, no. 8, pp. 2215 – 2227, Aug. 2011. Release
    @article{levorato-librino-2011-tcom,
      author = {Marco Levorato and Federico Librino and Michele Zorzi},
      title = {Integrated Cooperative Opportunistic Packet Forwarding and Distributed Error Control in {MIMO} Ad Hoc Networks},
      journal = {IEEE Transactions on Communications},
      volume = {59},
      number = {8},
      pages = {2215--2227},
      month = aug,
      year = {2011},
      doi = {10.1109/tcomm.2011.061311.090705},
    }
  • Marco Levorato
    Daniel O’Neill
    Andrea Goldsmith
    Urbashi Mitra
    M. Levorato, D. O’Neill, A. Goldsmith, and U. Mitra, Optimization of ARQ Protocols in Interference Networks With QoS Constraints, in Proceedings of the IEEE International Conference on Communications (ICC), Kyoto, Japan, Jun. 2011. Release
    @inproceedings{levorato-oneill-2011-icc,
      author = {Marco Levorato and Daniel O'Neill and Andrea Goldsmith and Urbashi Mitra},
      title = {Optimization of {ARQ} Protocols in Interference Networks With {QoS} Constraints},
      booktitle = {Proceedings of the IEEE International Conference on Communications (ICC)},
      address = {Kyoto, Japan},
      month = jun,
      year = {2011},
      doi = {10.1109/icc.2011.5963420},
    }
  • Jalil Seifali Harsini
    Farshad Lahouti
    Marco Levorato
    Michele Zorzi
    J. S. Harsini, F. Lahouti, M. Levorato, and M. Zorzi, Analysis of Non-Cooperative and Cooperative Type II Hybrid ARQ Protocols With AMC Over Correlated Fading, IEEE Transactions on Wireless Communications, vol. 10, no. 3, pp. 877 – 889, Mar. 2011. Release
    @article{harsini-lahouti-2011-twc,
      author = {Jalil Seifali Harsini and Farshad Lahouti and Marco Levorato and Michele Zorzi},
      title = {Analysis of Non-Cooperative and Cooperative Type {II} Hybrid {ARQ} Protocols With {AMC} Over Correlated Fading},
      journal = {IEEE Transactions on Wireless Communications},
      volume = {10},
      number = {3},
      pages = {877--889},
      month = mar,
      year = {2011},
      doi = {10.1109/twc.2011.010411.100328},
    }
  • Nicolò Michelusi
    Osvaldo Simeone
    Marco Levorato
    Petar Popovski
    Michele Zorzi
    N. Michelusi, O. Simeone, M. Levorato, P. Popovski, and M. Zorzi, Optimal Cognitive Transmission Exploiting Redundancy in the Primary ARQ Process, in Proceedings of the Information Theory and Applications Workshop (ITA), San Diego, CA, Feb. 2011. Release
    @inproceedings{michelusi-simeone-2011-ita,
      author = {Nicol{\`o} Michelusi and Osvaldo Simeone and Marco Levorato and Petar Popovski and Michele Zorzi},
      title = {Optimal Cognitive Transmission Exploiting Redundancy in the Primary {ARQ} Process},
      booktitle = {Proceedings of the Information Theory and Applications Workshop (ITA)},
      address = {San Diego, CA},
      month = feb,
      year = {2011},
      doi = {10.1109/ita.2011.5743628},
    }
  • Sina Firouzabadi
    Marco Levorato
    Daniel O’Neill
    Andrea Goldsmith
    S. Firouzabadi, M. Levorato, D. O’Neill, and A. Goldsmith, Learning Interference Strategies in Cognitive ARQ Networks, in Proceedings of the IEEE Global Communications Conference (GLOBECOM), Miami, Florida, Dec. 2010. Release
    @inproceedings{firouzabadi-levorato-2011-globecom,
      author = {Sina Firouzabadi and Marco Levorato and Daniel O'Neill and Andrea Goldsmith},
      title = {Learning Interference Strategies in Cognitive {ARQ} Networks},
      booktitle = {Proceedings of the IEEE Global Communications Conference (GLOBECOM)},
      address = {Miami, Florida},
      month = dec,
      year = {2010},
      doi = {10.1109/glocom.2010.5683502},
    }

2010

  • Marco Levorato
    Leonardo Badia
    Urbashi Mitra
    Michele Zorzi
    M. Levorato, L. Badia, U. Mitra, and M. Zorzi, An Analysis of Cognitive Networks for Unslotted Time and Reactive Users, in Proceedings of the IEEE International Conference on Mobile Ad Hoc and Sensor Systems (MASS), San Francisco, California, Nov. 2010. Release
    @inproceedings{levorato-badia-2010-mass,
      author = {Marco Levorato and Leonardo Badia and Urbashi Mitra and Michele Zorzi},
      title = {An Analysis of Cognitive Networks for Unslotted Time and Reactive Users},
      booktitle = {Proceedings of the IEEE International Conference on Mobile Ad Hoc and Sensor Systems (MASS)},
      address = {San Francisco, California},
      month = nov,
      year = {2010},
      doi = {10.1109/mass.2010.5664008},
    }
  • Daniel O’Neill
    Marco Levorato
    Andrea Goldsmith
    Urbashi Mitra
    D. O’Neill, M. Levorato, A. Goldsmith, and U. Mitra, Residential Demand Response Using Reinforcement Learning, in Proceedings of the IEEE International Conference on Smart Grid Communications (SmartGridComm), Gaithersburg, Maryland, Oct. 2010. Release
    @inproceedings{oneill-levorato-2010-smartgridcomm,
      author = {Daniel O'Neill and Marco Levorato and Andrea Goldsmith and Urbashi Mitra},
      title = {Residential Demand Response Using Reinforcement Learning},
      booktitle = {Proceedings of the IEEE International Conference on Smart Grid Communications (SmartGridComm)},
      address = {Gaithersburg, Maryland},
      month = oct,
      year = {2010},
      doi = {10.1109/smartgrid.2010.5622078},
    }
  • Jalil Seifali Harsini
    Farshad Lahouti
    Michele Zorzi
    Marco Levorato
    J. S. Harsini, F. Lahouti, M. Zorzi, and M. Levorato, A Type II Hybrid ARQ Protocol With Adaptive Modulation and Coding for Time-Correlated Fading Channels: Analysis and Design, in Proceedings of the IEEE International Conference on Communications (ICC), Cape Town, South Africa, May 2010. Release
    @inproceedings{harsini-lahouti-2010-icc,
      author = {Jalil Seifali Harsini and Farshad Lahouti and Michele Zorzi and Marco Levorato},
      title = {A Type {II} Hybrid {ARQ} Protocol With Adaptive Modulation and Coding for Time-Correlated Fading Channels: Analysis and Design},
      booktitle = {Proceedings of the IEEE International Conference on Communications (ICC)},
      address = {Cape Town, South Africa},
      month = may,
      year = {2010},
      doi = {10.1109/icc.2010.5501889},
    }
  • Leonardo Badia
    Nicola Baldo
    Marco Levorato
    Michele Zorzi
    L. Badia, N. Baldo, M. Levorato, and M. Zorzi, A Markov Framework for Error Control Techniques Based on Selective Retransmission in Video Transmission Over Wireless, IEEE Journal on Selected Areas in Communications, vol. 28, no. 3, pp. 488 – 500, Apr. 2010. Release
    @article{badia-baldo-2010-jsac,
      author = {Leonardo Badia and Nicola Baldo and Marco Levorato and Michele Zorzi},
      title = {A Markov Framework for Error Control Techniques Based on Selective Retransmission in Video Transmission Over Wireless},
      journal = {IEEE Journal on Selected Areas in Communications},
      volume = {28},
      number = {3},
      pages = {488--500},
      month = apr,
      year = {2010},
      doi = {10.1109/jsac.2010.100419},
    }
  • Leonardo Badia
    Marco Levorato
    Federico Librino
    Michele Zorzi
    L. Badia, M. Levorato, F. Librino, and M. Zorzi, Cooperation Techniques for Wireless Systems From a Networking Perspective, IEEE Wireless Communications Magazine, vol. 17, no. 2, pp. 89 – 96, Apr. 2010. Release
    @article{badia-levorato-2010-wirelessmag,
      author = {Leonardo Badia and Marco Levorato and Federico Librino and Michele Zorzi},
      title = {Cooperation Techniques for Wireless Systems From a Networking Perspective},
      journal = {IEEE Wireless Communications Magazine},
      volume = {17},
      number = {2},
      pages = {89--96},
      month = apr,
      year = {2010},
      doi = {10.1109/mwc.2010.5450665},
    }

2009

  • Marco Levorato
    Leonardo Badia
    Michele Zorzi
    M. Levorato, L. Badia, and M. Zorzi, On the Channel Statistics in Hybrid ARQ Systems for Correlated Channels, in Proceedings of the IEEE Information Theory Workshop (ITW), Taormina, Italy, Oct. 2009. Release
    @inproceedings{levorato-badia-2009-itw,
      author = {Marco Levorato and Leonardo Badia and Michele Zorzi},
      title = {On the Channel Statistics in Hybrid {ARQ} Systems for Correlated Channels},
      booktitle = {Proceedings of the IEEE Information Theory Workshop (ITW)},
      address = {Taormina, Italy},
      month = oct,
      year = {2009},
      doi = {10.1109/itw.2009.5351471},
    }
  • Marco Levorato
    Osvaldo Simeone
    Urbashi Mitra
    Michele Zorzi
    M. Levorato, O. Simeone, U. Mitra, and M. Zorzi, Cooperation and Coordination in Cognitive Networks With Packet Retransmission, in Proceedings of the IEEE Information Theory Workshop (ITW), Taormina, Italy, Oct. 2009. Release
    @inproceedings{levorato-simeone-2009-itw,
      author = {Marco Levorato and Osvaldo Simeone and Urbashi Mitra and Michele Zorzi},
      title = {Cooperation and Coordination in Cognitive Networks With Packet Retransmission},
      booktitle = {Proceedings of the IEEE Information Theory Workshop (ITW)},
      address = {Taormina, Italy},
      month = oct,
      year = {2009},
      doi = {10.1109/itw.2009.5351412},
    }
  • Marco Levorato
    Osvaldo Simeone
    Urbashi Mitra
    M. Levorato, O. Simeone, and U. Mitra, Interference Management via Rate Splitting and HARQ Over Time-Varying Fading Channels, in Proceedings of the ACM International Conference on Mobile Computing and Networking (MobiCom), Beijing, China, Sep. 2009. Release
    @inproceedings{levorato-simeone-2009-mobicom,
      author = {Marco Levorato and Osvaldo Simeone and Urbashi Mitra},
      title = {Interference Management via Rate Splitting and {HARQ} Over Time-Varying Fading Channels},
      booktitle = {Proceedings of the ACM International Conference on Mobile Computing and Networking (MobiCom)},
      address = {Beijing, China},
      month = sep,
      year = {2009},
      doi = {10.1145/1614235.1614242},
    }
  • Marco Levorato
    Urbashi Mitra
    Michele Zorzi
    M. Levorato, U. Mitra, and M. Zorzi, Cognitive Interference Management in Retransmission-Based Wireless Networks, in Proceedings of the Allerton Conference on Communication, Control and Computing, Monticello, Illinois, Sep. – Oct. 2009. Release
    @inproceedings{levorato-mitra-2009-allerton,
      author = {Marco Levorato and Urbashi Mitra and Michele Zorzi},
      title = {Cognitive Interference Management in Retransmission-Based Wireless Networks},
      booktitle = {Proceedings of the Allerton Conference on Communication, Control and Computing},
      address = {Monticello, Illinois},
      month = sep # {--} # oct,
      year = {2009},
      doi = {10.1109/allerton.2009.5394850},
    }
  • Stefano Tomasin
    Marco Levorato
    Michele Zorzi
    S. Tomasin, M. Levorato, and M. Zorzi, Steady State Analysis of Coded Cooperative Networks With HARQ Protocol, IEEE Transactions on Communications, vol. 57, no. 8, pp. 2391 – 2401, Aug. 2009. Release
    @article{tomasin-levorato-2009-tcom,
      author = {Stefano Tomasin and Marco Levorato and Michele Zorzi},
      title = {Steady State Analysis of Coded Cooperative Networks With {HARQ} Protocol},
      journal = {IEEE Transactions on Communications},
      volume = {57},
      number = {8},
      pages = {2391--2401},
      month = aug,
      year = {2009},
      doi = {10.1109/tcomm.2008.08.070478},
    }
  • Leonardo Badia
    Marco Levorato
    Michele Zorzi
    L. Badia, M. Levorato, and M. Zorzi, A Channel Representation Method for the Study of Hybrid Retransmission-Based Error Control, IEEE Transactions on Communications, vol. 57, no. 7, pp. 1959 – 1971, Jul. 2009. Release
    @article{badia-levorato-2009-tcom,
      author = {Leonardo Badia and Marco Levorato and Michele Zorzi},
      title = {A Channel Representation Method for the Study of Hybrid Retransmission-Based Error Control},
      journal = {IEEE Transactions on Communications},
      volume = {57},
      number = {7},
      pages = {1959--1971},
      month = jul,
      year = {2009},
      doi = {10.1109/tcomm.2009.07.070587},
    }
  • Marco Levorato
    Michele Zorzi
    M. Levorato and M. Zorzi, On the Performance of Ad Hoc Networks With Multiuser Detection, Rate Control and Hybrid ARQ, IEEE Transactions on Wireless Communications, vol. 8, no. 6, pp. 2938 – 2949, Jun. 2009. Release
    @article{levorato-zorzi-2009-twc,
      author = {Marco Levorato and Michele Zorzi},
      title = {On the Performance of Ad Hoc Networks With Multiuser Detection, Rate Control and Hybrid {ARQ}},
      journal = {IEEE Transactions on Wireless Communications},
      volume = {8},
      number = {6},
      pages = {2938--2949},
      month = jun,
      year = {2009},
      doi = {10.1109/twc.2009.080036},
    }
  • Leonardo Badia
    Marco Levorato
    Michele Zorzi
    L. Badia, M. Levorato, and M. Zorzi, Analysis of Selective Retransmission Techniques for Differentially Encoded Data, in Proceedings of the IEEE International Conference on Communications (ICC), Dresden, Germany, Jun. 2009. Release
    @inproceedings{badia-levorato-2009-icc,
      author = {Leonardo Badia and Marco Levorato and Michele Zorzi},
      title = {Analysis of Selective Retransmission Techniques for Differentially Encoded Data},
      booktitle = {Proceedings of the IEEE International Conference on Communications (ICC)},
      address = {Dresden, Germany},
      month = jun,
      year = {2009},
      doi = {10.1109/icc.2009.5198746},
    }
  • Marco Levorato
    Andrea Munari
    Michele Zorzi
    M. Levorato, A. Munari, and M. Zorzi, On the Effectiveness of Cooperation in Carrier Sense-Based Ad Hoc Networks, in Proceedings of the IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON), Rome, Italy, Jun. 2009. Release
    @inproceedings{levorato-munari-2009-secon,
      author = {Marco Levorato and Andrea Munari and Michele Zorzi},
      title = {On the Effectiveness of Cooperation in Carrier Sense-Based Ad Hoc Networks},
      booktitle = {Proceedings of the IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON)},
      address = {Rome, Italy},
      month = jun,
      year = {2009},
      doi = {10.1109/sahcn.2009.5168953},
    }
  • Federico Librino
    Marco Levorato
    Michele Zorzi
    F. Librino, M. Levorato, and M. Zorzi, An Algorithmic Solution for Computing Circle Intersection Areas and Its Applications to Wireless Communications, in Proceedings of the IEEE International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt), Seoul, Korea, Jun. 2009. Release
    @inproceedings{librino-levorato-2009-wiopt,
      author = {Federico Librino and Marco Levorato and Michele Zorzi},
      title = {An Algorithmic Solution for Computing Circle Intersection Areas and Its Applications to Wireless Communications},
      booktitle = {Proceedings of the IEEE International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)},
      address = {Seoul, Korea},
      month = jun,
      year = {2009},
      doi = {10.1109/wiopt.2009.5291627},
    }
  • Leonardo Badia
    Paolo Casari
    Marco Levorato
    Michele Zorzi
    L. Badia, P. Casari, M. Levorato, and M. Zorzi, Analysis of an Automatic Repeat Request Scheme Addressing Long Delay Channels, in Proceedings of the IEEE International Conference on Advanced Information Networking and Applications (AINA) Workshops, Bradford, UK, May 2009. Release
    @inproceedings{badia-casari-2009-aina,
      author = {Leonardo Badia and Paolo Casari and Marco Levorato and Michele Zorzi},
      title = {Analysis of an Automatic Repeat Request Scheme Addressing Long Delay Channels},
      booktitle = {Proceedings of the IEEE International Conference on Advanced Information Networking and Applications (AINA) Workshops},
      address = {Bradford, UK},
      month = may,
      year = {2009},
      doi = {10.1109/waina.2009.172},
    }
  • Marco Levorato
    Urbashi Mitra
    Michele Zorzi
    M. Levorato, U. Mitra, and M. Zorzi, On Optimal Control of Wireless Networks With Multiuser Detection, Hybrid ARQ and Distortion Constraints, in Proceedings of the IEEE International Conference on Computer Communications (INFOCOM), Rio de Janeiro, Brazil, Apr. 2009. Release
    @inproceedings{levorato-mitra-2009-infocom,
      author = {Marco Levorato and Urbashi Mitra and Michele Zorzi},
      title = {On Optimal Control of Wireless Networks With Multiuser Detection, Hybrid {ARQ} and Distortion Constraints},
      booktitle = {Proceedings of the IEEE International Conference on Computer Communications (INFOCOM)},
      address = {Rio de Janeiro, Brazil},
      month = apr,
      year = {2009},
      doi = {10.1109/infcom.2009.5062114},
    }

2008

  • Paolo Casari
    Marco Levorato
    Michele Zorzi
    P. Casari, M. Levorato, and M. Zorzi, MAC/PHY Cross-Layer Design of MIMO Ad Hoc Networks With Layered Multiuser Detection, IEEE Transactions on Wireless Communications, vol. 7, no. 11, pp. 4596 – 4607, Nov. 2008. Release
    @article{casari-levorato-2008-twc,
      author = {Paolo Casari and Marco Levorato and Michele Zorzi},
      title = {{MAC}/{PHY} Cross-Layer Design of {MIMO} Ad Hoc Networks With Layered Multiuser Detection},
      journal = {IEEE Transactions on Wireless Communications},
      volume = {7},
      number = {11},
      pages = {4596--4607},
      month = nov,
      year = {2008},
      doi = {10.1109/t-wc.2008.070600},
    }
  • Leonardo Badia
    Marco Levorato
    Michele Zorzi
    L. Badia, M. Levorato, and M. Zorzi, Markov Analysis of Selective Repeat Type II Hybrid ARQ Using Block Codes, IEEE Transactions on Communications, vol. 56, no. 9, pp. 1434 – 1441, Sep. 2008. Release
    @article{badia-levorato-2008-tcom,
      author = {Leonardo Badia and Marco Levorato and Michele Zorzi},
      title = {Markov Analysis of Selective Repeat Type {II} Hybrid {ARQ} Using Block Codes},
      journal = {IEEE Transactions on Communications},
      volume = {56},
      number = {9},
      pages = {1434--1441},
      month = sep,
      year = {2008},
      doi = {10.1109/tcomm.2008.060374},
    }
  • Marco Levorato
    Stefano Tomasin
    Michele Zorzi
    M. Levorato, S. Tomasin, and M. Zorzi, Cooperative Spatial Multiplexing for Ad Hoc Networks With Hybrid ARQ: Design and Performance Analysis, IEEE Transactions on Communications, vol. 56, no. 9, pp. 1545 – 1555, Sep. 2008. Release
    @article{levorato-tomasin-2008-tcom,
      author = {Marco Levorato and Stefano Tomasin and Michele Zorzi},
      title = {Cooperative Spatial Multiplexing for Ad Hoc Networks With Hybrid {ARQ}: Design and Performance Analysis},
      journal = {IEEE Transactions on Communications},
      volume = {56},
      number = {9},
      pages = {1545--1555},
      month = sep,
      year = {2008},
      doi = {10.1109/tcomm.2008.060447},
    }
  • Michele Zorzi
    Federico Librino
    Marco Levorato
    M. Zorzi, F. Librino, and M. Levorato, Cooperation in UMTS Cellular Networks: A Practical Perspective, in Proceedings of the IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Cannes, France, Sep. 2008, invited paper. Release
    @inproceedings{zorzi-librino-2008-pimrc,
      author = {Michele Zorzi and Federico Librino and Marco Levorato},
      title = {Cooperation in {UMTS} Cellular Networks: A Practical Perspective},
      booktitle = {Proceedings of the IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)},
      note = {invited paper},
      address = {Cannes, France},
      month = sep,
      year = {2008},
      doi = {10.1109/pimrc.2008.4699937},
    }
  • Paolo Casari
    Marco Levorato
    Daniele Mazzi
    Michele Zorzi
    P. Casari, M. Levorato, D. Mazzi, and M. Zorzi, On the Design of Routing Protocols in MIMO Ad Hoc Networks Under Uniform and Correlated Traffic, in Proceedings of the International Wireless Communications and Mobile Computing Conference (IWCMC), Creta, Greece, Aug. 2008. Release
    @inproceedings{casari-levorato-2008-iwcmc,
      author = {Paolo Casari and Marco Levorato and Daniele Mazzi and Michele Zorzi},
      title = {On the Design of Routing Protocols in {MIMO} Ad Hoc Networks Under Uniform and Correlated Traffic},
      booktitle = {Proceedings of the International Wireless Communications and Mobile Computing Conference (IWCMC)},
      address = {Creta, Greece},
      month = aug,
      year = {2008},
      doi = {10.1109/iwcmc.2008.48},
    }
  • Marco Levorato
    Leonardo Badia
    Michele Zorzi
    M. Levorato, L. Badia, and M. Zorzi, Efficient Quantization for Feedback Controlled Networks With Type II Hybrid ARQ, in Proceedings of the IEEE Workshop on Resource Allocation in Wireless Networks (RAWNET), Berlin, Germany, Apr. 2008. Release
    @inproceedings{levorato-badia-2008-rawnet,
      author = {Marco Levorato and Leonardo Badia and Michele Zorzi},
      title = {Efficient Quantization for Feedback Controlled Networks With Type {II} Hybrid {ARQ}},
      booktitle = {Proceedings of the IEEE Workshop on Resource Allocation in Wireless Networks (RAWNET)},
      address = {Berlin, Germany},
      month = apr,
      year = {2008},
      doi = {10.1109/wiopt.2008.4586038},
    }
  • Marco Levorato
    Michele Zorzi
    M. Levorato and M. Zorzi, On Error Control Schemes for Ad Hoc Networks With Multiuser Detection and Rate Control, in Proceedings of the Conference on Information Sciences and Systems (CISS), Princeton, New Jersey, Mar. 2008. Release
    @inproceedings{levorato-zorzi-2008-ciss,
      author = {Marco Levorato and Michele Zorzi},
      title = {On Error Control Schemes for Ad Hoc Networks With Multiuser Detection and Rate Control},
      booktitle = {Proceedings of the Conference on Information Sciences and Systems (CISS)},
      address = {Princeton, New Jersey},
      month = mar,
      year = {2008},
      doi = {10.1109/ciss.2008.4558606},
    }
  • Marco Levorato
    Michele Zorzi
    M. Levorato and M. Zorzi, Performance Analysis of Type II Hybrid ARQ With Low-Density Parity-Check Codes, in Proceedings of the International Symposium on Communications, Control, and Signal Processing (ISCCSP), St. Julians, Malta, Mar. 2008. Release
    @inproceedings{levorato-zorzi-2008-isccsp,
      author = {Marco Levorato and Michele Zorzi},
      title = {Performance Analysis of Type {II} Hybrid {ARQ} With Low-Density Parity-Check Codes},
      booktitle = {Proceedings of the International Symposium on Communications, Control, and Signal Processing (ISCCSP)},
      address = {St. Julians, Malta},
      month = mar,
      year = {2008},
      doi = {10.1109/isccsp.2008.4537333},
    }
  • Marco Levorato
    Michele Zorzi
    M. Levorato and M. Zorzi, Recursive Analysis of Ad Hoc Networks With Packet Queueing, Channel Contention and Hybrid ARQ, in Proceedings of the Information Theory and Applications Workshop (ITA), San Diego, California, Jan. – Feb. 2008. Release
    @inproceedings{levorato-zorzi-2008-ita,
      author = {Marco Levorato and Michele Zorzi},
      title = {Recursive Analysis of Ad Hoc Networks With Packet Queueing, Channel Contention and Hybrid {ARQ}},
      booktitle = {Proceedings of the Information Theory and Applications Workshop (ITA)},
      address = {San Diego, California},
      month = jan # {--} # feb,
      year = {2008},
      doi = {10.1109/ita.2008.4601098},
    }

2007

  • Marco Levorato
    Paolo Casari
    Stefano Tomasin
    Michele Zorzi
    M. Levorato, P. Casari, S. Tomasin, and M. Zorzi, Physical Layer Approximations for Cross-Layer Performance Analysis in MIMO-BLAST Ad Hoc Networks, IEEE Transactions on Wireless Communications, vol. 6, no. 12, pp. 4390 – 4400, Dec. 2007. Release
    @article{levorato-casari-2007-twc,
      author = {Marco Levorato and Paolo Casari and Stefano Tomasin and Michele Zorzi},
      title = {Physical Layer Approximations for Cross-Layer Performance Analysis in {MIMO}-{BLAST} Ad Hoc Networks},
      journal = {IEEE Transactions on Wireless Communications},
      volume = {6},
      number = {12},
      pages = {4390--4400},
      month = dec,
      year = {2007},
      doi = {10.1109/twc.2007.060211},
    }
  • Federico Librino
    Marco Levorato
    Michele Zorzi
    F. Librino, M. Levorato, and M. Zorzi, Distributed Cooperative Routing and Hybrid ARQ in MIMO-BLAST Ad Hoc Networks, in Proceedings of the IEEE Global Communications Conference (GLOBECOM), Washington, DC, Nov. 2007. Release
    @inproceedings{librino-levorato-2007-globecom,
      author = {Federico Librino and Marco Levorato and Michele Zorzi},
      title = {Distributed Cooperative Routing and Hybrid {ARQ} in {MIMO}-{BLAST} Ad Hoc Networks},
      booktitle = {Proceedings of the IEEE Global Communications Conference (GLOBECOM)},
      address = {Washington, DC},
      month = nov,
      year = {2007},
      doi = {10.1109/glocom.2007.128},
    }
  • Leonardo Badia
    Marco Levorato
    Michele Zorzi
    L. Badia, M. Levorato, and M. Zorzi, An Improved Channel Quantization Method for Performance Evaluation of Incremental Redundancy HARQ Based on Reliable Channel Regions, in Proceedings of the Allerton Conference on Communication, Control and Computing, Monticello, Illinois, Sep. 2007.
    @inproceedings{badia-levorato-2007-allerton,
      author = {Leonardo Badia and Marco Levorato and Michele Zorzi},
      title = {An Improved Channel Quantization Method for Performance Evaluation of Incremental Redundancy {HARQ} Based on Reliable Channel Regions},
      booktitle = {Proceedings of the Allerton Conference on Communication, Control and Computing},
      address = {Monticello, Illinois},
      month = sep,
      year = {2007},
    }
  • Stefano Tomasin
    Marco Levorato
    Michele Zorzi
    S. Tomasin, M. Levorato, and M. Zorzi, Coded Cooperation for Ad Hoc Networks With Spatial Multiplexing, in Proceedings of the IEEE International Conference on Communications (ICC), Glasgow, UK, Jun. 2007. Release
    @inproceedings{tomasin-levorato-2007-icc,
      author = {Stefano Tomasin and Marco Levorato  and Michele Zorzi},
      title = {Coded Cooperation for Ad Hoc Networks With Spatial Multiplexing},
      booktitle = {Proceedings of the IEEE International Conference on Communications (ICC)},
      address = {Glasgow, UK},
      month = jun,
      year = {2007},
      doi = {10.1109/icc.2007.784},
    }
  • Stefano Tomasin
    Marco Levorato
    Michele Zorzi
    S. Tomasin, M. Levorato, and M. Zorzi, Analysis of Outage Probability for Cooperative Networks With HARQ, in Proceedings of the IEEE International Symposium on Information Theory (ISIT), Nice, France, Jun. 2007. Release
    @inproceedings{tomasin-levorato-2007-isit,
      author = {Stefano Tomasin and Marco Levorato  and Michele Zorzi},
      title = {Analysis of Outage Probability for Cooperative Networks With {HARQ}},
      booktitle = {Proceedings of the IEEE International Symposium on Information Theory (ISIT)},
      address = {Nice, France},
      month = jun,
      year = {2007},
      doi = {10.1109/isit.2007.4557629},
    }
  • Marco Levorato
    Stefano Tomasin
    Michele Zorzi
    M. Levorato, S. Tomasin, and M. Zorzi, Strategies and Tradeoffs for Coded Cooperation in Wireless Networks, in Proceedings of the IEEE International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt), Limassol, Cyprus, Apr. 2007. Release
    @inproceedings{levorato-tomasin-2007-wiopt,
      author = {Marco Levorato and Stefano Tomasin and Michele Zorzi},
      title = {Strategies and Tradeoffs for Coded Cooperation in Wireless Networks},
      booktitle = {Proceedings of the IEEE International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)},
      address = {Limassol, Cyprus},
      month = apr,
      year = {2007},
      doi = {10.1109/wiopt.2007.4480100},
    }

2006

  • Leonardo Badia
    Marco Levorato
    Michele Zorzi
    L. Badia, M. Levorato, and M. Zorzi, Analytical Investigation With Markov Models of Selective Repeat Truncated Type II Hybrid ARQ, in Proceedings of the IEEE Global Communications Conference (GLOBECOM), San Francisco, California, Nov. – Dec. 2006. Release
    @inproceedings{badia-levorato-2006-globecom,
      author = {Leonardo Badia and Marco Levorato and Michele Zorzi},
      title = {Analytical Investigation With Markov Models of Selective Repeat Truncated Type {II} Hybrid {ARQ}},
      booktitle = {Proceedings of the IEEE Global Communications Conference (GLOBECOM)},
      address = {San Francisco, California},
      month = nov # {--} # dec,
      year = {2006},
      doi = {10.1109/glocom.2006.914},
    }
  • Marco Levorato
    Paolo Casari
    Michele Zorzi
    M. Levorato, P. Casari, and M. Zorzi, On the Performance of Access Strategies for MIMO Ad Hoc Networks, in Proceedings of the IEEE Global Communications Conference (GLOBECOM), San Francisco, California, Nov. – Dec. 2006. Release
    @inproceedings{levorato-casari-2006-globecom,
      author = {Marco Levorato and Paolo Casari and Michele Zorzi},
      title = {On the Performance of Access Strategies for {MIMO} Ad Hoc Networks},
      booktitle = {Proceedings of the IEEE Global Communications Conference (GLOBECOM)},
      address = {San Francisco, California},
      month = nov # {--} # dec,
      year = {2006},
      doi = {10.1109/glocom.2006.934},
    }
  • Marco Levorato
    Stefano Tomasin
    Michele Zorzi
    M. Levorato, S. Tomasin, and M. Zorzi, Analysis of Cooperative Spatial Multiplexing for Ad Hoc Networks With Adaptive Hybrid ARQ, in Proceedings of the IEEE Vehicular Technology Conference (VTC), Montreal, Canada, Sep. 2006. Release
    @inproceedings{levorato-tomasin-2006-vtc,
      author = {Marco Levorato and Stefano Tomasin and Michele Zorzi},
      title = {Analysis of Cooperative Spatial Multiplexing for Ad Hoc Networks With Adaptive Hybrid {ARQ}},
      booktitle = {Proceedings of the IEEE Vehicular Technology Conference (VTC)},
      address = {Montreal, Canada},
      month = sep,
      year = {2006},
      doi = {10.1109/vtcf.2006.452},
    }
  • Paolo Casari
    Marco Levorato
    Michele Zorzi
    P. Casari, M. Levorato, and M. Zorzi, DSMA: An Access Method for MIMO Ad Hoc Networks Based on Distributed Scheduling, in Proceedings of the International Wireless Communications and Mobile Computing Conference (IWCMC), Vancouver, Canada, Jul. 2006. Release
    @inproceedings{casari-levorato-2006-iwcmc,
      author = {Paolo Casari and Marco Levorato and Michele Zorzi},
      title = {{DSMA}: An Access Method for {MIMO} Ad Hoc Networks Based on Distributed Scheduling},
      booktitle = {Proceedings of the International Wireless Communications and Mobile Computing Conference (IWCMC)},
      address = {Vancouver, Canada},
      month = jul,
      year = {2006},
      doi = {10.1145/1143549.1143637},
    }
  • Marco Levorato
    Paolo Casari
    Stefano Tomasin
    Michele Zorzi
    M. Levorato, P. Casari, S. Tomasin, and M. Zorzi, An Approximate Approach for Layered Space-Time Multiuser Detection Performance and Its Application to MIMO Ad Hoc Networks, in Proceedings of the IEEE International Conference on Communications (ICC), Istanbul, Turkey, Jun. 2006. Release
    @inproceedings{levorato-casari-2006-icc,
      author = {Marco Levorato and Paolo Casari and Stefano Tomasin and Michele Zorzi},
      title = {An Approximate Approach for Layered Space-Time Multiuser Detection Performance and Its Application to {MIMO} Ad Hoc Networks},
      booktitle = {Proceedings of the IEEE International Conference on Communications (ICC)},
      address = {Istanbul, Turkey},
      month = jun,
      year = {2006},
      doi = {10.1109/icc.2006.255649},
    }
  • Marco Levorato
    Paolo Casari
    Stefano Tomasin
    Michele Zorzi
    M. Levorato, P. Casari, S. Tomasin, and M. Zorzi, Analysis of Spatial Multiplexing for Cross-Layer Design of MIMO Ad Hoc Networks, in Proceedings of the IEEE Vehicular Technology Conference (VTC), Melbourne, Australia, May 2006. Release
    @inproceedings{levorato-casari-2006-vtc,
      author = {Marco Levorato and Paolo Casari and Stefano Tomasin and Michele Zorzi},
      title = {Analysis of Spatial Multiplexing for Cross-Layer Design of {MIMO} Ad Hoc Networks},
      booktitle = {Proceedings of the IEEE Vehicular Technology Conference (VTC)},
      address = {Melbourne, Australia},
      month = may,
      year = {2006},
      doi = {10.1109/vetecs.2006.1683014},
    }

2005

  • Paolo Casari
    Marco Levorato
    Michele Zorzi
    P. Casari, M. Levorato, and M. Zorzi, On the Implications of Layered Space-Time Multiuser Detection on the Design of MAC Protocols for Ad Hoc Networks, in Proceedings of the IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Berlin, Germany, Sep. 2005. Release
    @inproceedings{casari-levorato-2005-pimrc,
      author = {Paolo Casari and Marco Levorato and Michele Zorzi},
      title = {On the Implications of Layered Space-Time Multiuser Detection on the Design of {MAC} Protocols for Ad Hoc Networks},
      booktitle = {Proceedings of the IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)},
      address = {Berlin, Germany},
      month = sep,
      year = {2005},
      doi = {10.1109/pimrc.2005.1651661},
    }
  • Paolo Casari
    Marco Levorato
    Michele Zorzi
    P. Casari, M. Levorato, and M. Zorzi, Some Issues Concerning MAC Design in Ad Hoc Networks With MIMO Communications, in Proceedings of the Wireless Personal Multimedia Conference (WPMC), Aalborg, Denmark, Sep. 2005.
    @inproceedings{casari-levorato-2005-wpmc,
      author = {Paolo Casari and Marco Levorato and Michele Zorzi},
      title = {Some Issues Concerning {MAC} Design in Ad Hoc Networks With {MIMO} Communications},
      booktitle = {Proceedings of the Wireless Personal Multimedia Conference (WPMC)},
      address = {Aalborg, Denmark},
      month = sep,
      year = {2005},
    }
  • Michele Rossi
    Paolo Casari
    Marco Levorato
    Michele Zorzi
    M. Rossi, P. Casari, M. Levorato, and M. Zorzi, Multicast Streaming Over 3G Cellular Networks Through Multi-Channel Transmissions: Proposals and Performance Evaluation, in Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC), New Orleans, Louisiana, Mar. 2005. Release
    @inproceedings{rossi-casari-2005-wcnc,
      author = {Michele Rossi and Paolo Casari and Marco Levorato and Michele Zorzi},
      title = {Multicast Streaming Over {3G} Cellular Networks Through Multi-Channel Transmissions: Proposals and Performance Evaluation},
      booktitle = {Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC)},
      address = {New Orleans, Louisiana},
      month = mar,
      year = {2005},
      doi = {10.1109/wcnc.2005.1424779},
    }

All references in BibTeX