Non-dominated sorting based multi-objective clustering algorithm for WSN

Li Han, Weidong Wang, Yinghai Zhang, Chaowei Wang, Cai Qin
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引用次数: 1

Abstract

In wireless sensor networks (WSN), energy efficiency is one of the major challenges because of the difficulty of charging nodes in monitored area. Clustering sensor nodes is an effective topology control method to reduce energy consumption of sensor nodes. Studies of clustering algorithm usually focus on the whole lifetime but ignore the stable time (the time at which the first node dies) in WSN. This study proposes a clustering algorithm which aims to improve the stability and extend the lifetime of the network simultaneously by balancing and reducing the energy consumption for each node in WSN. The proposed algorithm is based on an improved Non-dominated sorting genetic algorithm-II (NSGA-II) which is a multi-objective optimization algorithm to achieve several goals. Five objective functions are used to optimize energy consumption and load balance. In the improved NSGA-II, a weight value is adopted to evaluate the clustering solutions after the crowding distance to sort the individuals in every generation more reasonably. According to the simulation results, the proposed algorithm achieves longer stable period and longer lifetime than LEACH & clustering algorithm based on traditional NSGA-II.
基于非支配排序的WSN多目标聚类算法
在无线传感器网络(WSN)中,由于监控区域内节点的充电困难,能效成为主要挑战之一。传感器节点聚类是降低传感器节点能耗的一种有效的拓扑控制方法。聚类算法的研究通常着眼于整个生命周期,而忽略了WSN的稳定时间(第一个节点死亡的时间)。本文提出了一种聚类算法,通过平衡和降低WSN中各节点的能量消耗,同时提高网络的稳定性和延长网络的生命周期。该算法基于改进的非支配排序遗传算法- ii (NSGA-II),该算法是一种多目标优化算法,可实现多个目标。利用5个目标函数优化能耗和负载平衡。在改进的NSGA-II中,采用一个权值对拥挤距离后的聚类解进行评价,使每代个体的排序更加合理。仿真结果表明,与基于传统NSGA-II的LEACH和聚类算法相比,该算法具有更长的稳定周期和更长的生存期。
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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