Whale Optimization Approach for Optimization Problem In Distributed Wireless Sensor Network

Lotfi Baidar, Abdellatif Rahmoun, P. Lorenz, M. Mihoubi
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引用次数: 7

Abstract

Recently, Node localization has played a vital role in wireless sensor networks (WSN), where the node's coordinates have mostly required before sensing operation. Sensor devices are randomly deployed in the network for monitoring task. The crucial objective of localization is to determine the position of the sensor nodes based on a few landmark nodes. Node localization problem is formulated as an optimization problem and metaheuristic techniques are called to deal with the issue in multidimensional space, in this paper, the Whale Optimization Algorithm (WOA) is proposed to deal with the challenge, furthermore, the capability of auto localization is highly requested. WOA computes iteratively the node's positions based on a multistage approach to browse the whole region of the network. Deploying this algorithm on a large WSN with hundreds of sensors shows good performance in terms of node localization. the simulation result proved the good performance of WOA in term of localization error and computing time.
分布式无线传感器网络优化问题的鲸鱼优化方法
近年来,节点定位在无线传感器网络(WSN)中起着至关重要的作用,在传感操作之前,节点的坐标通常是必需的。传感器设备随机部署在网络中执行监控任务。定位的关键目标是根据几个地标节点确定传感器节点的位置。将节点定位问题表述为一个优化问题,利用元启发式技术在多维空间中处理节点定位问题,提出了鲸鱼优化算法(WOA)来解决节点定位问题,并对节点的自动定位能力提出了很高的要求。WOA基于多阶段浏览整个网络区域的方法迭代计算节点的位置。将该算法部署在具有数百个传感器的大型WSN上,在节点定位方面表现出良好的性能。仿真结果证明了WOA在定位误差和计算时间方面具有良好的性能。
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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