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

doi:10.1109/WCNC.2016.7564864

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

Electrical Engineering

Queen Mary University of London
Middlesex University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

11 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 language	British English
Title of host publication	2016 IEEE Wireless Communications and Networking Conference, WCNC 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781467398145
DOIs	https://doi.org/10.1109/WCNC.2016.7564864
State	Published - 12 Sep 2016
Event	2016 IEEE Wireless Communications and Networking Conference, WCNC 2016 - Doha, Qatar Duration: 3 Apr 2016 → 7 Apr 2016

Publication series

Name	IEEE Wireless Communications and Networking Conference, WCNC
Volume	2016-September
ISSN (Print)	1525-3511

Conference

Conference	2016 IEEE Wireless Communications and Networking Conference, WCNC 2016
Country/Territory	Qatar
City	Doha
Period	3/04/16 → 7/04/16

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

battery capacity
cluster
energy efficiency
IoT systems
network lifetime
QPSO

Access to Document

10.1109/WCNC.2016.7564864

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Cite this

Song, L., Chai, K. K., Chen, Y., Loo, J., Jimaa, S., & Schormans, J. (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 2016 Article 7564864 (IEEE Wireless Communications and Networking Conference, WCNC; Vol. 2016-September). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WCNC.2016.7564864

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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\%.",

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Song, L, Chai, KK, Chen, Y, Loo, J, Jimaa, S & Schormans, J 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 2016., 7564864, IEEE Wireless Communications and Networking Conference, WCNC, vol. 2016-September, Institute of Electrical and Electronics Engineers Inc., 2016 IEEE Wireless Communications and Networking Conference, WCNC 2016, Doha, Qatar, 3/04/16. https://doi.org/10.1109/WCNC.2016.7564864

QPSO-based energy-Aware clustering scheme in the capillary networks for Internet of Things systems. / Song, Liumeng; Chai, Kok Keong; Chen, Yue et al.
2016 IEEE Wireless Communications and Networking Conference, WCNC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. 7564864 (IEEE Wireless Communications and Networking Conference, WCNC; Vol. 2016-September).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Chai, Kok Keong

AU - Chen, Yue

AU - Loo, Jonathan

AU - Jimaa, Shihab

AU - Schormans, John

PY - 2016/9/12

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N2 - 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%.

AB - 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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ER -

Song L, Chai KK, Chen Y, Loo J, Jimaa S, Schormans J. QPSO-based energy-Aware clustering scheme in the capillary networks for Internet of Things systems. In 2016 IEEE Wireless Communications and Networking Conference, WCNC 2016. Institute of Electrical and Electronics Engineers Inc. 2016. 7564864. (IEEE Wireless Communications and Networking Conference, WCNC). doi: 10.1109/WCNC.2016.7564864

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

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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