rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Distributed network structure estimation using consensus methods
  name:
    name part: Zhang, Sai
    name part: (Electrical engineering student)
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Banavar, Mahesh K.
    role:
      role term: author.
  name:
    name part: Spanias, Andreas
    role:
      role term: author.
  name:
    name part: Tepedelenlioğlu, Cihan
    role:
      role term: author.
  name:
    name part: Morgan & Claypool Publishers
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: cau
    date issued: 2018
    issuance: monographic
  language:
    language term: eng
  physical description:
    reformatting quality: access
    form: remote
    extent: 1 online resource (xi, 76 pages) : illustrations (chiefly color)
  abstract: 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.
  table of contents: 1. Introduction -- 1.1. Wireless sensor networks -- 1.2. Applications -- 1.3. Consensus methods in distributed WSNs -- 1.4. Network structure estimation -- 1.5. Organization of the book
  table of contents: 2. Review of consensus and network structure estimation -- 2.1. Graph representation of distributed WSNs -- 2.2. Review of consensus algorithms -- 2.3. Review of network structure estimation
  table of contents: 3. Distributed node counting in WSNs -- 3.1. System model -- 3.2. Distributed node counting based on L2 norm estimation -- 3.3. Performance analysis -- 3.4. Simulation results
  table of contents: 4. Noncentralized estimation of degree distribution -- 4.1. System model -- 4.2. Consensus-based degree distribution estimation -- 4.3. Estimation of degree matrix -- 4.4. Performance analysis -- 4.5. Simulations
  table of contents: 5. Network center and coverage region estimation -- 5.1. System model -- 5.2. Estimation of network center and radius -- 5.3. Performance analysis -- 5.4. Simulations -- 5.5. Discussion : global data structure estimation -- 6. Conclusions -- A. Notation.
  target audience: specialized
  note: Sai Zhang, Cihan Tepedelenlioglu, Andreas Spanias, Mahesh Banavar.
  note: Part of: Synthesis digital library of engineering and computer science.
  note: Abstract freely available; full-text restricted to subscribers or individual document purchasers.
  note: Compendex
  note: Google book search
  note: Google scholar
  note: INSPEC
  note: Also available in print.
  note: Mode of access: World Wide Web.
  note: System requirements: Adobe Acrobat Reader.
  note: Includes bibliographical references (pages 59-74).
  subject:
    topic: Electronic data processing
    topic: Distributed processing
  subject:
    topic: Wireless sensor networks
  subject:
    topic: Internet-of-Things (IoT)
  subject:
    topic: diffusion adaptation
  subject:
    topic: node counting
  subject:
    topic: wireless sensor networks
  classification: TK7872.D48 .Z534 2018
  classification: 681/.2
  related item:
    note: Compendex
  related item:
    note: Google book search
  related item:
    note: Google scholar
  related item:
    note: INSPEC
  related item:
    title info:
      title: Synthesis digital library of engineering and computer science
  related item:
    title info:
      title: Synthesis lectures on communications ; #13
  identifier: 9781681732909
  identifier: 9781681732916
  identifier: https://dx.doi.org/10.2200/S00829ED1V01Y201802COM013
  access condition: Abstract freely available; full-text restricted to subscribers or individual document purchasers.
  record info:
    record content source: CaBNVSL
    record creation date: 180330
    record change date: 20210304161511.0
    record identifier: in00004034433
    language of cataloging:
      language term: eng