基于粒子群优化的无线传感器网络聚类降低能耗

Amin Rostami, Mohammad Hossin Mottar, I. Azad
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引用次数: 29

摘要

无线传感器网络由大量功能有限的小节点组成。在这种类型的网络中,最重要的问题是能量限制。在这方面已经进行了一些研究,聚类是最有效的解决方案之一。聚类的目标是将网络划分为多个部分,每个部分都有一个簇头(CH)。承担簇头采集、数据聚合和向基站传输的任务。本文提出了一种基于粒子群优化(PSO)算法的传感器网络聚类方法,利用最优适应度函数来延长网络寿命。该算法使用的参数有剩余能量密度、到基站的距离、到簇头的簇内距离。仿真结果表明,与LEACH、CHEF、PSO-MV等协议相比,该方法在网络寿命和能量消耗方面更有效。
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WIRELESS SENSOR NETWORK CLUSTERING USING PARTICLES SWARM OPTIMIZATION FOR REDUCING ENERGY CONSUMPTION
Wireless sensor networks (WSN ) is composed of a large number of small nodes with limited functionality. The most important issue in this type of networks is energy constraints. In this area several researches have been done from which clustering is one of the most effective solutions. The goal of clustering is to divide network into sections each of which has a cluster head (CH). The task of cluster heads collection, data aggregation and transmission to the base station is undertaken. In this paper, we introduce a new approach for clustering sensor networks based on Particle Swarm Optimization (PSO) algorithm using the optimal fitness function, which aims to extend network lifetime. The parameters used in this algorithm are residual energy density, the distance from the base station, intra-cluster distance from the cluster head. Simulation results show that the proposed method is more effective compared to protocols such as (LEACH, CHEF, PSO-MV) in terms of network lifetime and energy consumption.
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