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

Liumeng Song, Kok Keong Chai, Yue Chen, Jonathan Loo, Shihab Jimaa, John Schormans

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

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%.

Original languageBritish English
Title of host publication2016 IEEE Wireless Communications and Networking Conference, WCNC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467398145
DOIs
StatePublished - 12 Sep 2016
Event2016 IEEE Wireless Communications and Networking Conference, WCNC 2016 - Doha, Qatar
Duration: 3 Apr 20167 Apr 2016

Publication series

NameIEEE Wireless Communications and Networking Conference, WCNC
Volume2016-September
ISSN (Print)1525-3511

Conference

Conference2016 IEEE Wireless Communications and Networking Conference, WCNC 2016
Country/TerritoryQatar
CityDoha
Period3/04/167/04/16

Keywords

  • battery capacity
  • cluster
  • energy efficiency
  • IoT systems
  • network lifetime
  • QPSO

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