QPSO-based energy-aware clustering scheme in the capillary networks for Internet of Things systems

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Song, Liumeng, Chai, Kok Keong, Chen, Yue, Loo, Jonathan ORCID: https://orcid.org/0000-0002-2197-8126, Jimaa, Shihab and Schormans, John (2016) QPSO-based energy-aware clustering scheme in the capillary networks for Internet of Things systems. In: 2016 IEEE Wireless Communications and Networking Conference (WCNC), 03-06 April 2016, Doha, Qatar.

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Official URL: https://doi.org/10.1109/WCNC.2016.7564864

Abstract

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%.

Item Type:	Conference or Workshop Item (Paper)
ISSN:	1558-2612
ISBN:	9781467398152
Identifier:	10.1109/WCNC.2016.7564864
Identifier:	10.1109/WCNC.2016.7564864
Additional Information:	© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Keywords:	IoT systems, cluster, QPSO, energy efficiency, network lifetime, battery capacity
Subjects:	Computing > Systems > Computer networking Computing > Systems Computing
Depositing User:	Jonathan Loo
Date Deposited:	21 Jun 2017 15:32
Last Modified:	04 Nov 2024 12:35
URI:	https://repository.uwl.ac.uk/id/eprint/3471