An Energy Efficient Tour Construction Using Restricted k-Means Clustering Algorithm for Mobile Sink in Wireless Sensor Networks

Aram Rasul, Abdulbasit K. Al-Talabani
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Abstract

abstract There has been much research on efficient energy utilisation to prolong the life-span of wireless sensor networks and other tiny devices, with various techniques deployed to address energy consumption issues. The aim of this paper is to build on previous research and further investigate the use of a mobile sink for data collection in wireless sensor networks. We aim to find an optimal path for a mobile sink to collect a single packet from each sensor via a single hop and return back to the starting point such that, subject to the length constraint L, total energy wastage is minimised. We have previously referred to this problem as the minimum energy cost mobile sink restricted tour problem and showed that this is NP-hard. We were inspired by the concept of the k-means clustering algorithm and propose a restricted k-means clustering algorithm. In this approach, we first divide the sensing field into a set of k clusters such that the radius of each cluster is R, where R is the maximum transmission range of the sensor. We iteratively increase the value of k until all the sensors are covered under the length constraint. Simplicity, efficiency, and flexibility are the most important and distinctive features of this algorithm. The technique is implemented to evaluate the algorithm and compare it to our previous algorithm. Our simulation results outperformed the previous technique.
基于受限k均值聚类算法的无线传感器网络移动Sink节能游构造
为了延长无线传感器网络和其他微型设备的寿命,人们对有效利用能源进行了大量研究,并部署了各种技术来解决能源消耗问题。本文的目的是在以前的研究基础上,进一步研究在无线传感器网络中使用移动接收器进行数据收集。我们的目标是为移动接收器找到一个最佳路径,通过单个跳从每个传感器收集单个数据包,然后返回到起点,这样,受长度约束L的约束,总能量浪费最小化。我们之前将此问题称为最小能量成本移动汇受限巡回问题,并表明这是NP-hard问题。我们受到k-means聚类算法概念的启发,提出了一种受限的k-means聚类算法。在这种方法中,我们首先将传感场划分为k个簇,每个簇的半径为R,其中R为传感器的最大传输范围。我们迭代地增加k的值,直到在长度约束下覆盖所有传感器。简单、高效、灵活是该算法最重要的特点。该技术用于评估算法并将其与之前的算法进行比较。我们的模拟结果优于以前的技术。
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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