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mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Wireless sensor networks
    sub title: evolutionary algorithms for optimizing performance
  name:
    name part: Edla, Damodar Reddy
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Kongara, Mahesh Chowdary
    role:
      role term: author.
  name:
    name part: Lipare, Amruta
    role:
      role term: author.
  name:
    name part: Kuppili, Venkatanareshbabu
    role:
      role term: author.
  name:
    name part: K, Kannadasan
    role:
      role term: author.
  name:
    name part: Taylor & Francis
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: flu
    date issued: 2021
    edition: First edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (xii, 134 pages) : illustrations (black and white)
  abstract: Wireless Sensor Networks: Evolutionary Algorithms for Optimizing Performance provides an integrative overview of bio-inspired algorithms and their applications in the area of Wireless Sensor Networks (WSN). Along with the usage of the WSN, the number of risks and challenges occurs while deploying any WSN. Therefore, to defeat these challenges some of the bio-inspired algorithms are applied and discussed in this book. Discussion includes a broad, integrated perspective on various challenges and issues in WSN and also impact of bio-inspired algorithms on the lifetime of the WSN. It creates interdisciplinary theory, concepts, definitions, models and findings involved in WSN and Bio-inspired algorithms making it an essential guide and reference. It includes various WSN examples making the book accessible to a broader interdisciplinary readership. The book offers comprehensive coverage of the most essential topics, including: Evolutionary algorithms Swarm intelligence Hybrid algorithms Energy efficiency in WSN Load balancing of gateways Localization Clustering and routing Designing fitness functions according to the issues in WSN. The book explains about practices of shuffled complex evolution algorithm, shuffled frog leaping algorithm, particle swarm optimization and dolphin swarm optimization to defeat various challenges in WSN. The author elucidates how we must transform our thinking, illuminating the benefits and opportunities offered by bio-inspired approaches to innovation and learning in the area of WSN. This book serves as a reference book for scientific investigators who shows an interest in evolutionary computation and swarm intelligence as well as issues and challenges in WSN.
  table of contents: Introduction. Literature Survey. Load Balancing of Gateways using Shuffed Complex Evolution Algorithm. Novel Fitness Function for SCE Algorithm based Energy Efficiency in WSN. An Efficient Load Balancing of Gateways using Improved SFLA for WSNs. SCE-PSO based Clustering Technique for Load Balancing in WSN. PSO based Routing with Novel Fitness Function for Improving Lifetime of WSN. M-Curves Path Planning for Mobile Anchor Node and Localization of Sensor Nodes using DSA. Conclusion and Future Research. Bibliography. Index.
  note: Damodar Reddy Edla, Mahesh Chowdary Kongara, Amruta Lipare, Venkatanareshbabu Kuppili, Kannadasan K.
  note: "A Chapman & Hall book."
  note: Includes bibliographical references and index.
  note: Dr. Damodar Reddy Edla is an Assistant Professsor in the Department of Computer Science and Engineering at National Institute of Technology Goa, India. He received M.Sc. Degree from the University of Hyderabad in 2006, M.Tech. in Computer Application and Ph. D. Degree in Computer Science and Engineering from Indian Schoolof Mines Dhanbad in 2009 and 2013 respectively. His research interests include Cognitive Neuroscience, Data Mining, Wireless Sensor Networks and Brain-Computer Interface. He has published more than 100 research articles in reputed journals and international conferences. He is the senior member of IEEE and IACSIT. Heis also Editorial Board member of several international journals. Mahesh Chowdary Kongara received the B.Tech. Degree in Computer Science and Engineering from SreeVidyanikethan Engineering College, Tirupati, Andhra Pradesh and the M.Tech. Degree in Department of Computer Science and Engineering from National Institute of Technology Goa, India in 2017. He is currently a Full-Time Research Scholar with the Department of Computer Science and Engineering, National Institute of TechnologyGoa. His research interests include Soft Computing, Wireless Sensor Networks, Internet of Things. Amruta Lipare has received the B.Tech. Degree in Information Technology from Rajarambapu Institute of Technology, Sakharale, Maharashtra, in 2015, and the M.Tech. Degree in Computer Science and Engineering from National Institute of Technology, Goa, in 2017. She is currently a Full-Time Research Scholar with the Department of Computer Science and Engineering, National Institute of Technology Goa. India. Her research interest includes Soft Computing, Wireless Sensor Networks, Evolutionary Computations and Swarm Intelligence. Dr. Venkatanareshbabu Kuppili, Ph D (IIT Delhi), is with the Machine Learning Group, Department of CSE, NIT Goa, India, where he is currently an Assistant Professor. He was with Evalueserve pvt. ltd, as a Senior Research Associate. He is also a…
  subject:
    topic: Wireless sensor networks
  subject:
    topic: Computer algorithms
  subject:
    topic: Algorithms
  subject:
    topic: Réseaux de capteurs sans fil
  subject:
    topic: Algorithmes
  subject:
    topic: algorithms
  subject:
    topic: COMPUTERS / Computer Engineering
  subject:
    topic: COMPUTERS / Computer Science
  subject:
    topic: MATHEMATICS / General
  subject:
    topic: Algorithms
  subject:
    topic: Computer algorithms
  subject:
    topic: Wireless sensor networks
  classification: TK7872.D48 E35 2021eb
  classification: 681/.2
  identifier: 9781000214031
  identifier: 1000214036
  identifier: 9780429324611
  identifier: 0429324618
  identifier: 9781000214079
  identifier: 1000214079
  identifier: 9781000214055
  identifier: 1000214052
  identifier: 9780367342418
  identifier: 0367342413
  identifier: 9781000214079 Ingram Content Group
  identifier: 9780429324611 Taylor & Francis
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: UKMGB
    record creation date: 200917
    record change date: 20241108170022.7
    record identifier: in00005525928
    language of cataloging:
      language term: eng