QPSO-based Energy-aware Clustering Scheme in the Capillary Networks for Internet of Things Systems

被引：0

作者：

Song, Liumeng ^{[1
]}

Chai, Kok Keong ^{[1
]}

Chen, Yue ^{[1
]}

Loo, Jonathan ^{[2
]}

Jimaa, Shihab ^{[3
]}

Schormans, John ^{[1
]}

机构：

[1] Queen Mary Univ London, Sch Elect Engn & Comp Sci, London, England

[2] Middlesex Univ, Sch Engn & Informat Sci, London, England

[3] Khalifa Univ Sci Technol & Res, Dept Elect & Comp Engn, Sharjah, U Arab Emirates

来源：

2016 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE | 2016年

关键词：

Terms-IoT systems; cluster; QPSO; energy efficiency; network lifetime; battery capacity; EFFICIENCY;

D O I：

暂无

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

Energy efficiency is a crucial challenge in cluster-based capillary networks for Internet of Things (IoT) systems, where the cluster heads (CHs) selection has great impact on the network performance. It is an optimization problem to find the optimum number of CHs as well as which devices are selected as CHs. In this paper, we formulate the clustering problem into the CHs selection procedure with the aim of maximizing the average network lifetime in every round. In particular, we propose a novel CHs selection scheme based on QPSO and investigate how effective it is to prolong network lifetime and reserve the overall battery capacity. The simulation results prove that the proposed QPSO outperforms other evolutionary algorithms and can improve the network lifetime by almost 10%.

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页数：6

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