Sensor Node Placement in Wireless Sensor Network Using Multi-objective Territorial Predator Scent Marking Algorithm

H. Zainol Abidin, Norashidah Md Din, I. M. Yassin, H. A. Omar, Nurul Asyikin Mohamed Radzi, S. K. Sadon

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Optimum sensor node placement for wireless sensor network (WSN) in a monitored area is needed for cost-effective deployment. The location of sensor nodes must be able to offer maximum coverage and connectivity with minimum energy consumption. This paper proposes a sensor node placement approach that utilizes a new biologically inspired multi-objective optimization algorithm that imitates the behaviour of a territorial predator in marking their territories with their odours known as multi-objective territorial predator scent marking algorithm (MOTPSMA). The algorithm uses the maximum coverage and minimum energy consumption objective functions with subject to full connectivity. A simulation study has been carried out to compare the performance of the proposed algorithm with the multi-objective evolutionary algorithm with fuzzy dominance-based decomposition and an integer linear programming algorithm. Simulation results show that WSN deployed using the MOTPSMA sensor node placement algorithm outperforms the performance of the other two algorithms in terms of coverage, connectivity and energy usage.

Original languageEnglish
Pages (from-to)6317-6325
Number of pages9
JournalArabian Journal for Science and Engineering
Volume39
Issue number8
DOIs
Publication statusPublished - 01 Jan 2014

Fingerprint

Sensor nodes
Wireless sensor networks
Energy utilization
Odors
Multiobjective optimization
Evolutionary algorithms
Linear programming
Decomposition
Costs

All Science Journal Classification (ASJC) codes

  • General

Cite this

@article{f43ba3efe29142dc876ae6cacaf78404,
title = "Sensor Node Placement in Wireless Sensor Network Using Multi-objective Territorial Predator Scent Marking Algorithm",
abstract = "Optimum sensor node placement for wireless sensor network (WSN) in a monitored area is needed for cost-effective deployment. The location of sensor nodes must be able to offer maximum coverage and connectivity with minimum energy consumption. This paper proposes a sensor node placement approach that utilizes a new biologically inspired multi-objective optimization algorithm that imitates the behaviour of a territorial predator in marking their territories with their odours known as multi-objective territorial predator scent marking algorithm (MOTPSMA). The algorithm uses the maximum coverage and minimum energy consumption objective functions with subject to full connectivity. A simulation study has been carried out to compare the performance of the proposed algorithm with the multi-objective evolutionary algorithm with fuzzy dominance-based decomposition and an integer linear programming algorithm. Simulation results show that WSN deployed using the MOTPSMA sensor node placement algorithm outperforms the performance of the other two algorithms in terms of coverage, connectivity and energy usage.",
author = "{Zainol Abidin}, H. and {Md Din}, Norashidah and Yassin, {I. M.} and Omar, {H. A.} and {Mohamed Radzi}, {Nurul Asyikin} and Sadon, {S. K.}",
year = "2014",
month = "1",
day = "1",
doi = "10.1007/s13369-014-1292-3",
language = "English",
volume = "39",
pages = "6317--6325",
journal = "Arabian Journal for Science and Engineering",
issn = "1319-8025",
publisher = "Springer Berlin",
number = "8",

}

Sensor Node Placement in Wireless Sensor Network Using Multi-objective Territorial Predator Scent Marking Algorithm. / Zainol Abidin, H.; Md Din, Norashidah; Yassin, I. M.; Omar, H. A.; Mohamed Radzi, Nurul Asyikin; Sadon, S. K.

In: Arabian Journal for Science and Engineering, Vol. 39, No. 8, 01.01.2014, p. 6317-6325.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Sensor Node Placement in Wireless Sensor Network Using Multi-objective Territorial Predator Scent Marking Algorithm

AU - Zainol Abidin, H.

AU - Md Din, Norashidah

AU - Yassin, I. M.

AU - Omar, H. A.

AU - Mohamed Radzi, Nurul Asyikin

AU - Sadon, S. K.

PY - 2014/1/1

Y1 - 2014/1/1

N2 - Optimum sensor node placement for wireless sensor network (WSN) in a monitored area is needed for cost-effective deployment. The location of sensor nodes must be able to offer maximum coverage and connectivity with minimum energy consumption. This paper proposes a sensor node placement approach that utilizes a new biologically inspired multi-objective optimization algorithm that imitates the behaviour of a territorial predator in marking their territories with their odours known as multi-objective territorial predator scent marking algorithm (MOTPSMA). The algorithm uses the maximum coverage and minimum energy consumption objective functions with subject to full connectivity. A simulation study has been carried out to compare the performance of the proposed algorithm with the multi-objective evolutionary algorithm with fuzzy dominance-based decomposition and an integer linear programming algorithm. Simulation results show that WSN deployed using the MOTPSMA sensor node placement algorithm outperforms the performance of the other two algorithms in terms of coverage, connectivity and energy usage.

AB - Optimum sensor node placement for wireless sensor network (WSN) in a monitored area is needed for cost-effective deployment. The location of sensor nodes must be able to offer maximum coverage and connectivity with minimum energy consumption. This paper proposes a sensor node placement approach that utilizes a new biologically inspired multi-objective optimization algorithm that imitates the behaviour of a territorial predator in marking their territories with their odours known as multi-objective territorial predator scent marking algorithm (MOTPSMA). The algorithm uses the maximum coverage and minimum energy consumption objective functions with subject to full connectivity. A simulation study has been carried out to compare the performance of the proposed algorithm with the multi-objective evolutionary algorithm with fuzzy dominance-based decomposition and an integer linear programming algorithm. Simulation results show that WSN deployed using the MOTPSMA sensor node placement algorithm outperforms the performance of the other two algorithms in terms of coverage, connectivity and energy usage.

UR - http://www.scopus.com/inward/record.url?scp=84904861455&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84904861455&partnerID=8YFLogxK

U2 - 10.1007/s13369-014-1292-3

DO - 10.1007/s13369-014-1292-3

M3 - Article

VL - 39

SP - 6317

EP - 6325

JO - Arabian Journal for Science and Engineering

JF - Arabian Journal for Science and Engineering

SN - 1319-8025

IS - 8

ER -