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Erschienen in:
Wireless Sensor Network: Applications, Challenges, and Algorithms Kapitel lesen Erstes Kapitel lesen

2020 | OriginalPaper | Buchkapitel

12. Bio-inspired Algorithm for Multi-objective Optimization in Wireless Sensor Network

verfasst von : Anindita Raychaudhuri, Debashis De

Erschienen in: Nature Inspired Computing for Wireless Sensor Networks

Verlag: Springer Singapore

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Abstract

In recent days bio-inspired computing is playing an important role in the area of research. Especially bio-inspired algorithms which are inspired by the behavior of nature are massively used to perform optimization. Wireless Sensor Networks (WSN) are playing vital role in all sectors. Some crucial issues of WSN are clustering, optimal routing, dynamic allocation of motes, energy and lifetime optimization. Researchers are working for several years to resolve issues of WSN for better quality of service. Bio-inspired algorithms like Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) are playing important role in solving the issues of WSN. Still some algorithms are insufficiently studied. Bio-inspired computing is gradually gaining interest from researchers for its intelligence and adaptive nature. Although these algorithms have perceived a lot of attention from researchers in current years, the domain-specific understanding still needs to be improved for its establishment. In this chapter bio-inspired algorithms are discussed concisely with their importance in the field of wireless sensor networks.

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Vorheriges Kapitel Qualitative Survey on Sensor Node Deployment, Load Balancing and Energy Utilization in Sensor Network
Nächstes Kapitel TLBO Based Cluster-Head Selection for Multi-objective Optimization in Wireless Sensor Networks
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Metadaten
Titel
Bio-inspired Algorithm for Multi-objective Optimization in Wireless Sensor Network
verfasst von
Anindita Raychaudhuri
Debashis De
Copyright-Jahr
2020
Verlag
Springer Singapore
Buch
Nature Inspired Computing for Wireless Sensor Networks

Print ISBN: 978-981-15-2124-9

Electronic ISBN: 978-981-15-2125-6

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-981-15-2125-6_12

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