Balanced Clustering Approach with Energy Prediction and Round-Time Adaptation in Wireless Sensor Networks

IF 1 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS

International Journal of Communication Networks and Distributed Systems Pub Date : 2019-02-21 DOI:10.1504/IJCNDS.2019.10012413

Nassima Merabtine, D. Djenouri, D. Zegour, Billel Boumessaidia, Abdelghani Boutahraoui

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引用次数: 1

Abstract

This paper proposes three techniques to improve the energy efficiency of clustering protocols in wireless sensor networks (WSNs). The first technique reduces the periodic network re-clustering, the second adapts the rounds' durations to the cluster-heads' (CHs) residual energy, while the third one ensures fair and spatially balanced distribution of CHs over the network. For the purpose of performance evaluation, these techniques are implemented on TPSO-CR, one of the state-of-the-art clustering protocols. TPSO-CR, its enhanced version with the proposed techniques (ETPSO-CR) and LEACH-C are compared. The results demonstrate that the proposed solutions remarkably reduce and balance the total energy consumed in the network. Thereby, the time to the first node death is more than doubled in some scenarios. The improvements are ranging from 25% to 76% for several network lifetime metrics and the total number of received data at the base station is increased by 30%, on average.

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基于能量预测和周期自适应的无线传感器网络平衡聚类方法

本文提出了提高无线传感器网络中聚类协议能量效率的三种技术。第一种技术减少了周期性的网络重新聚类，第二种技术使轮的持续时间适应簇头(CHs)的剩余能量，而第三种技术保证了簇头在网络上的公平和空间平衡分布。为了进行性能评估，这些技术都是在最先进的聚类协议之一TPSO-CR上实现的。比较了TPSO-CR及其增强版(ETPSO-CR)和LEACH-C。结果表明，所提出的解决方案显著地降低和平衡了网络的总能耗。因此，在某些场景中，到第一个节点死亡的时间增加了一倍以上。对于几个网络生命周期指标，改进幅度从25%到76%不等，基站接收到的数据总数平均增加了30%。

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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来源期刊

International Journal of Communication Networks and Distributed Systems COMPUTER SCIENCE, INFORMATION SYSTEMS-

CiteScore

2.50

自引率

46.20%

发文量

期刊介绍： IJCNDS aims to improve the state-of-the-art of worldwide research in communication networks and distributed systems and to address the various methodologies, tools, techniques, algorithms and results. It is not limited to networking issues in telecommunications; network problems in other application domains such as biological networks, social networks, and chemical networks will also be considered. This feature helps in promoting interdisciplinary research in these areas.