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Whale Optimization Based Energy-Efficient Cluster Head Selection Algorithm for Wireless Sensor Networks.

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TLDR
An energy efficient cluster head selection algorithm which is based on Whale Optimization Algorithm called WOA-Clustering (WOA-C) is proposed and helps in selection of energy aware cluster heads based on a fitness function which considers the residual energy of the node and the sum of energy of adjacent nodes.
Abstract
Wireless Sensor Network (WSN) consists of many individual sensors that are deployed in the area of interest. These sensor nodes have major energy constraints as they are small and their battery can't be replaced. They collaborate together in order to gather, transmit and forward the sensed data to the base station. Consequently, data transmission is one of the biggest reasons for energy depletion in WSN. Clustering is one of the most effective techniques for energy efficient data transmission in WSN. In this paper, an energy efficient cluster head selection algorithm which is based on Whale Optimization Algorithm (WOA) called WOA-Clustering (WOA-C) is proposed. Accordingly, the proposed algorithm helps in selection of energy aware cluster heads based on a fitness function which considers the residual energy of the node and the sum of energy of adjacent nodes. The proposed algorithm is evaluated for network lifetime, energy efficiency, throughput and overall stability. Furthermore, the performance of WOA-C is evaluated against other standard contemporary routing protocols such as LEACH. Extensive simulations show the superior performance of the proposed algorithm in terms of residual energy, network lifetime and longer stability period.

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Citations
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Journal ArticleDOI

A comprehensive survey: Whale Optimization Algorithm and its applications

TL;DR: An overview of WOA is described in this paper, rooted from the bubble-net hunting strategy, besides an overview ofWOA applications that are used to solve optimization problems in various categories.
Journal ArticleDOI

Whale optimization algorithm: a systematic review of contemporary applications, modifications and developments

TL;DR: The review presented in the paper has the potential to motivate expert researchers to propose more novel WOA-based algorithms, and it can serve as an initial reading material for a novice researcher.
Journal ArticleDOI

Energy efficient protocol in wireless sensor network: optimized cluster head selection model

TL;DR: A new hybrid algorithm is proposed that hybridizes the concept of dragon fly and firefly algorithm algorithms, termed fire fly replaced position update in dragonfly, to develop a new clustering model with optimal cluster head selection by considering four major criteria like energy, delay, distance, and security.
Book ChapterDOI

Whale optimization algorithm: Theory, literature review, and application in designing photonic crystal filters

TL;DR: This chapter presents and analyzes the Whale Optimization Algorithm and tests the performance of WOA on several test functions and a real case study in the field of photonic crystal filter.
Journal ArticleDOI

Nature-Inspired Algorithms for Wireless Sensor Networks: A Comprehensive Survey

TL;DR: In this article, the authors compared the performance of two nature-inspired algorithms for getting optimal coverage in WSNs, i.e., the combined improved genetic algorithm and binary ant colony algorithm, and the lion optimization (LO) algorithm.
References
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Proceedings ArticleDOI

Energy-efficient communication protocol for wireless microsensor networks

TL;DR: The Low-Energy Adaptive Clustering Hierarchy (LEACH) as mentioned in this paper is a clustering-based protocol that utilizes randomized rotation of local cluster based station (cluster-heads) to evenly distribute the energy load among the sensors in the network.

Energy-efficient communication protocols for wireless microsensor networks

TL;DR: LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster based station (cluster-heads) to evenly distribute the energy load among the sensors in the network, is proposed.
Journal ArticleDOI

An application-specific protocol architecture for wireless microsensor networks

TL;DR: This work develops and analyzes low-energy adaptive clustering hierarchy (LEACH), a protocol architecture for microsensor networks that combines the ideas of energy-efficient cluster-based routing and media access together with application-specific data aggregation to achieve good performance in terms of system lifetime, latency, and application-perceived quality.
Journal ArticleDOI

The Whale Optimization Algorithm

TL;DR: Optimization results prove that the WOA algorithm is very competitive compared to the state-of-art meta-heuristic algorithms as well as conventional methods.
Proceedings ArticleDOI

PEGASIS: Power-efficient gathering in sensor information systems

TL;DR: PEGASIS (power-efficient gathering in sensor information systems), a near optimal chain-based protocol that is an improvement over LEACH, is proposed, where each node communicates only with a close neighbor and takes turns transmitting to the base station, thus reducing the amount of energy spent per round.
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