Multi-objective Optimization (MOO) approach for sensor node placement in WSN

Husna Zainol Abidin, Norashidah Md Din, Yanti Erana Jalil

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

It is desirable to position sensor nodes in a Wireless Sensor Network (WSN) to be able to provide maximum coverage with minimum energy consumption. However, these two aspects are contradicting and quite impossible to solve the placement problem with a single optimal decision. Thus, a Multi-objective Optimization (MOO) approach is needed to facilitate this. This paper studies the performance of a WSN sensor node placement problem solved with a new biologically inspired optimization technique that imitates the behavior of territorial predators in marking their territories with their odours known as Territorial Predator Scent Marking Algorithm (TPSMA). The simulation study is done for a single objective and multi-objective approaches. The MOO approach of TPSMA (MOTPSMA) deployed in this paper uses the minimum energy consumption and maximum coverage as the objective functions while the single objective approach TPSMA only considers maximum coverage. The performance of both approaches is then compared in terms of coverage ratio and total energy consumption. Simulation results show that the WSN deployed with the MOTPSMA is able to reduce the energy consumption although the coverage ratio is slightly lower than single approach TPSMA which only focuses on maximizing the coverage.

Original languageEnglish
Title of host publication2013, 7th International Conference on Signal Processing and Communication Systems, ICSPCS 2013 - Proceedings
PublisherIEEE Computer Society
ISBN (Print)9781479913190
DOIs
Publication statusPublished - 01 Jan 2013
Event2013 7th International Conference on Signal Processing and Communication Systems, ICSPCS 2013 - Gold Coast, QLD, Australia
Duration: 16 Dec 201318 Dec 2013

Other

Other2013 7th International Conference on Signal Processing and Communication Systems, ICSPCS 2013
CountryAustralia
CityGold Coast, QLD
Period16/12/1318/12/13

Fingerprint

Multiobjective optimization
Sensor nodes
Wireless sensor networks
Energy utilization
Odors

All Science Journal Classification (ASJC) codes

  • Signal Processing

Cite this

Abidin, H. Z., Md Din, N., & Jalil, Y. E. (2013). Multi-objective Optimization (MOO) approach for sensor node placement in WSN. In 2013, 7th International Conference on Signal Processing and Communication Systems, ICSPCS 2013 - Proceedings [6723994] IEEE Computer Society. https://doi.org/10.1109/ICSPCS.2013.6723994
Abidin, Husna Zainol ; Md Din, Norashidah ; Jalil, Yanti Erana. / Multi-objective Optimization (MOO) approach for sensor node placement in WSN. 2013, 7th International Conference on Signal Processing and Communication Systems, ICSPCS 2013 - Proceedings. IEEE Computer Society, 2013.
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Abidin, HZ, Md Din, N & Jalil, YE 2013, Multi-objective Optimization (MOO) approach for sensor node placement in WSN. in 2013, 7th International Conference on Signal Processing and Communication Systems, ICSPCS 2013 - Proceedings., 6723994, IEEE Computer Society, 2013 7th International Conference on Signal Processing and Communication Systems, ICSPCS 2013, Gold Coast, QLD, Australia, 16/12/13. https://doi.org/10.1109/ICSPCS.2013.6723994

Multi-objective Optimization (MOO) approach for sensor node placement in WSN. / Abidin, Husna Zainol; Md Din, Norashidah; Jalil, Yanti Erana.

2013, 7th International Conference on Signal Processing and Communication Systems, ICSPCS 2013 - Proceedings. IEEE Computer Society, 2013. 6723994.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abidin HZ, Md Din N, Jalil YE. Multi-objective Optimization (MOO) approach for sensor node placement in WSN. In 2013, 7th International Conference on Signal Processing and Communication Systems, ICSPCS 2013 - Proceedings. IEEE Computer Society. 2013. 6723994 https://doi.org/10.1109/ICSPCS.2013.6723994