基于变长遗传算法的无线传感器网络移动汇聚数据采集优化

Raj Anwit
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引用次数: 7

摘要

在无线传感器网络(WSN)中,利用移动接收器(MS)采集数据是一种有效的从传感器节点(SNs)采集数据的方法。使用MS有几个优点,例如,它有助于缓解sink hole问题,平衡网络的能量消耗,提高网络寿命等。MS必须通过WSN,并在SNs附近的一些预定义位置停下来,从SNs收集数据。在本篇论文中,我们提出了一种新的变长遗传算法(VLGA)来解决这个问题。该算法寻找逗留点的最优数量和位置,用于设计ms的行程,并与TSP算法进行了广泛的仿真比较。结果表明,VLGA算法在MS的路径长度和数据采集时间方面优于TSP算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Variable Length Genetic Algorithm approach to Optimize Data Collection using Mobile Sink in Wireless Sensor Networks
Data collection using mobile sink (MS) in wireless sensor network (WSN) is an efficient approach to collect data from sensor nodes (SNs). There are several advantages of using a MS like, it helps to alleviate the sink hole problem, balances energy consumption of the network, enhances network lifetime etc. The MS has to go through the WSN and collect data from SNs by stopping at some predefined locations from where SNs are in its vicinity. Finding the number of such locations is a fundamental problem in the path design of a MS. In this paper, we present a novel variable length gentic algorithm (VLGA) to find a solution to the problem. The algorithm finds the optimal number and location of sojourn points which are used to design the tour of the MS. The algorithm is simulated extensively and compared with the TSP algorithm. The results obtained shows better performance of VLGA over TSP algorithm in terms of path length and data collection time of the MS.
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