04629cam a22006251i 4500 9780429324611 FlBoTFG 20260210180823.0 m o d cr cnu---unuuu 200917s2021 flua ob 001 0 eng d OCoLC-P eng rda pn OCoLC-P 9781000214031 electronic book 1000214036 electronic book 9780429324611 electronic book 0429324618 electronic book 9781000214079 electronic publication 1000214079 electronic publication 9781000214055 Mobipocket electronic book 1000214052 Mobipocket electronic book 9780367342418 hardcover 0367342413 10.1201/9780429324611 doi (OCoLC)1202939663 (OCoLC)1226504940 (OCoLC-P)1202939663 TK7872.D48 E35 2021eb COM 059000 bisacsh COM 014000 bisacsh MAT 000000 bisacsh UB bicssc 681/.2 23 Edla, Damodar Reddy, author. Wireless sensor networks : evolutionary algorithms for optimizing performance / Damodar Reddy Edla, Mahesh Chowdary Kongara, Amruta Lipare, Venkatanareshbabu Kuppili, Kannadasan K. First edition. Boca Raton. FL : CRC Press, 2021. 1 online resource (xii, 134 pages) : illustrations (black and white) text txt rdacontent computer c rdamedia online resource cr rdacarrier "A Chapman & Hall book." 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. 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. OCLC-licensed vendor bibliographic record. Wireless sensor networks. Computer algorithms. 4948 COMPUTERS / Computer Engineering bisacsh COMPUTERS / Computer Science bisacsh MATHEMATICS / General bisacsh Kongara, Mahesh Chowdary, author. Lipare, Amruta, author. Kuppili, Venkatanareshbabu, author. K, Kannadasan, author. Taylor & Francis https://www.taylorfrancis.com/books/9780429324611 OCLC metadata license agreement http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf 91940 91939