Damodar Reddy Edla, Mahesh Chowdary Kongara, Amruta Lipare, Venkatanareshbabu Kuppili, Kannadasan K
Wireless Sensor Networks
Evolutionary Algorithms for Optimizing Performance
Damodar Reddy Edla, Mahesh Chowdary Kongara, Amruta Lipare, Venkatanareshbabu Kuppili, Kannadasan K
Wireless Sensor Networks
Evolutionary Algorithms for Optimizing Performance
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With the evolution of soft computing, bio-inspired algorithms have gained more attention in recent years. This book is aimed at undergraduates, graduates and researchers working in the domain of wireless networks.
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With the evolution of soft computing, bio-inspired algorithms have gained more attention in recent years. This book is aimed at undergraduates, graduates and researchers working in the domain of wireless networks.
Produktdetails
- Produktdetails
- Verlag: CRC Press
- Seitenzahl: 146
- Erscheinungstermin: 24. November 2020
- Englisch
- Abmessung: 234mm x 156mm x 10mm
- Gewicht: 386g
- ISBN-13: 9780367342418
- ISBN-10: 0367342413
- Artikelnr.: 59997960
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- gpsr@libri.de
- Verlag: CRC Press
- Seitenzahl: 146
- Erscheinungstermin: 24. November 2020
- Englisch
- Abmessung: 234mm x 156mm x 10mm
- Gewicht: 386g
- ISBN-13: 9780367342418
- ISBN-10: 0367342413
- Artikelnr.: 59997960
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- gpsr@libri.de
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 School of 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. He is also Editorial Board member of several international journals. Mahesh Chowdary Kongara received the B.Tech. Degree in Computer Science and Engineering from Sree Vidyanikethan 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 Technology Goa. 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 actively involved in teaching and research development for the Graduate Program in Computer Science and Engineering Department at the NIT Goa. He has authored several research papers published in reputed International journals and conferences. He is senior member of IEEE. Kannadasan has completed his B.Tech in Information Technology at SASTRA University, Tamilnadu and M.Tech in Computer Science and Engineering, National Institute of Technology, Goa. Currently, he is pursuing his PhD degree in National Institute of Technology, Tiruchirappalli. He is student member in IEEE and Secretary at IEEE Student branch, NIT Tiruchirappalli. His research interests include Machine Learning, Wireless Sensor Networks, Swarm optimization techniques, Brain-Computer Interface etc.
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.
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.
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.
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.