Impact of grey wolf optimization on WSN cluster formation and lifetime expansion

Marwa Sharawi, E. Emary
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引用次数: 31

Abstract

This work introduces a cluster head selection optimization model in wireless sensor networks (WSN). It applies the grey wolf optimization. The optimization of WSN cluster heads greatly influences the network life time. Grey wolf optimization(GWO) is a recently proposed optimizer that has a variety of successful applications. Therefore, adapted and applied in here to solve the CH selection problem. Suitable fitness function were employed to ensure coverage of the WSN and is fed to the GWO to find its optimum. Results of the introduced model is compared with the LEACH routing protocol. Four different deployments of the WSN are examined. Lifetime, residual energy and network throughput performance indicators are examined in our experiments as assessment indicators. The introduced system outperforms the LEACH in almost all topologies using the different indicators.
灰狼优化对WSN簇形成和寿命扩展的影响
介绍了一种无线传感器网络簇头选择优化模型。它应用了灰狼优化。无线传感器网络簇头的优化对网络寿命影响很大。灰狼优化(GWO)是最近提出的一种优化器,有各种成功的应用。因此,本文采用并应用于解决CH的选择问题。采用合适的适应度函数来保证WSN的覆盖范围,并将适应度函数馈送到GWO中求其最优。将模型的结果与LEACH路由协议进行了比较。研究了无线传感器网络的四种不同部署。在我们的实验中考察了寿命、剩余能量和网络吞吐量性能指标作为评估指标。引入的系统在使用不同指标的几乎所有拓扑中都优于LEACH。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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