A Joint Clustering and Routing Algorithm based on GA for Multi Objective Optimization in WSN

Marwa Fattoum, Zakia Jellali, L. N. Atallah
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引用次数: 4

Abstract

Reducing energy consumption is the most serious issue of the Wireless Sensors Networks (WSN) topology design due to the resources constraint. Genetic Algorithm (GA) is used as a suitable solution to better manage energy consumption and increase the whole network lifetime. In such context, a new joint Clustering and Routing algorithm based on GA for Multi Objective Optimization (CRMOGA) is proposed for finding the optimal network configuration. Simulation result proofs that the proposed CRMOGA approach performs better than LEACH and the recently proposed Two-Level Clustering (TLC) scheme and enhances the network lifetime.
基于遗传算法的WSN多目标优化联合聚类和路由算法
由于资源的限制,降低能量消耗是无线传感器网络(WSN)拓扑设计中最重要的问题。采用遗传算法(Genetic Algorithm, GA)可以更好地管理能耗,提高整个网络的生存期。在此背景下,提出了一种新的基于遗传算法的多目标优化聚类和路由联合算法(CRMOGA)来寻找最优网络配置。仿真结果表明,该方法优于LEACH和最近提出的两级聚类(TLC)方案,提高了网络的生存期。
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