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Distributed Network Structure Estimation Using Consensus Methods Andreas Spanias

Distributed Network Structure Estimation Using Consensus Methods

$2136.00

Medios de pago

    Distributed Network Structure Estimation Using Consensus Methods

    Editorial: Morgan & Claypool Publishers

    Idioma: Inglés

    ISBN: 9781681732916

    Formatos: PDF (con DRM de Adobe)

    Compatibles con: Windows, Mac, iOS, Android & eReaders

    $2136.00

    Medios de pago
      Distributed Network Structure Estimation Using Consensus Methods Andreas Spanias

      Distributed Network Structure Estimation Using Consensus Methods

      $2136.00

      Medios de pago

        Distributed Network Structure Estimation Using Consensus Methods

        Editorial: Morgan & Claypool Publishers

        Idioma: Inglés

        ISBN: 9781681732916

        Formatos: PDF (con DRM de Adobe)

        Compatibles con: Windows, Mac, iOS, Android & eReaders

        $2136.00

        Medios de pago
          Sinopsis
          The area of detection and estimation in a distributed wireless sensor network (WSN) has several applications, including military surveillance, sustainability, health monitoring, and Internet of Things (IoT). Compared with a wired centralized sensor network, a distributed WSN has many advantages including scalability and robustness to sensor node failures. In this book, we address the problem of estimating the structure of distributed WSNs. First, we provide a literature review in: (a) graph theory; (b) network area estimation; and (c) existing consensus algorithms, including average consensus and max consensus. Second, a distributed algorithm for counting the total number of nodes in a wireless sensor network with noisy communication channels is introduced. Then, a distributed network degree distribution estimation (DNDD) algorithm is described. The DNDD algorithm is based on average consensus and in-network empirical mass function estimation. Finally, a fully distributed algorithm for estimating the center and the coverage region of a wireless sensor network is described. The algorithms introduced are appropriate for most connected distributed networks. The performance of the algorithms is analyzed theoretically, and simulations are performed and presented to validate the theoretical results. In this book, we also describe how the introduced algorithms can be used to learn global data information and the global data region.
          Acerca de Andreas Spanias

          Arizona State University

          Acerca de Cihan Tepedelenlioglu

          Arizona State University

          Acerca de Mahesh Banavar

          Mahesh Banavar received a B.E. degree in telecommunications engineering from Visvesvaraya Technological University, Karnataka, India, in 2005 and M.S. and Ph.D. degrees, both in electrical engineering, from Arizona State University, Tempe, in 2007 and 2010, respectively. He is currently an Assistant Professor in the Department of Electrical and Computer Engineering at Clarkson University, Potsdam, NY. His interests include node localization, detection and estimation algorithms, and performance analysis of distributed sensor algorithms for wireless sensor networks. Dr. Banavar is a recipient of the Teaching Excellence Award from the Graduate and Professional Student Association at Arizona State University and the Outstanding Teaching Award from the Eta Kappa Nu chapter at Clarkson University. He is also a member of MENSA and the Eta Kappa Nu honor society.

          Acerca de Sai Zhang

          Sai Zhang received a B.S. degree in electrical and information engineering from Huazhong University of Science and Technology, Wuhan, China, in 2012 and an M.S. degree in electrical engineering from Arizona State University, Tempe, AZ, in 2014. From 2014 to 2017 he was a research assistant at Arizona State University, where he completed his Ph.D. degree in electrical engineering. His research interests include distributed computation in wireless sensor networks, performance analysis of distributed consensus algorithms, and wireless communications.

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