Multi-objective clustering and routing for maximizing lifetime of wireless sensor networks

Meng Li, Chaowei Wang, Weidong Wang, Cai Qin, Xiuhua Li
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引用次数: 3

Abstract

Multi-objective optimization is a technology of multiple criteria decision making, which is suitable for routing and clustering in wireless sensor networks (WSNs). In WSNs, clustering need to consider nodes' energy, the distance to the cluster heads (CHs), etc. Additionally, routing need to consider nodes' energy and the hops to the base station (BS), etc. However, existing algorithms just consider some of the factors or convert multiple factors into a single objective function resulting in worse performances. In this paper, an improved non-dominated sorting particle swarm optimizer for multi-objective optimization (INSPSO) is proposed to prolong network lifetime. We also adopt a non-uniform clustering strategy to avoid hot spot problem caused by multi-hop communication. Then, we simulate the proposed algorithm and compare with some existing clustering and routing algorithms to demonstrate the advantages of our algorithm.
无线传感器网络多目标聚类与路由优化
多目标优化是一种多准则决策技术,适用于无线传感器网络中的路由和聚类问题。在wsn中,聚类需要考虑节点的能量、到簇头的距离等。此外,路由还需要考虑节点的能量和到基站的跳数等。然而,现有算法只考虑部分因素或将多个因素转化为单个目标函数,导致性能较差。为了延长网络的生存期,提出了一种改进的非支配排序粒子群多目标优化算法(INSPSO)。为了避免多跳通信带来的热点问题,采用了非均匀聚类策略。然后,我们对所提出的算法进行了仿真,并与现有的一些聚类和路由算法进行了比较,以证明所提出算法的优越性。
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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