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

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dc.citedby18
dc.contributor.authorAbidin H.Z.en_US
dc.contributor.authorDin N.M.en_US
dc.contributor.authorJalil Y.E.en_US
dc.contributor.authorid52165115900en_US
dc.contributor.authorid9335429400en_US
dc.contributor.authorid55257996600en_US
dc.date.accessioned2023-12-28T04:12:48Z
dc.date.available2023-12-28T04:12:48Z
dc.date.issued2013
dc.description.abstractIt 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. � 2013 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo6723994
dc.identifier.doi10.1109/ICSPCS.2013.6723994
dc.identifier.scopus2-s2.0-84903830291
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84903830291&doi=10.1109%2fICSPCS.2013.6723994&partnerID=40&md5=6c43d9e582d8bb69f1b9199657939832
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/29371
dc.publisherIEEE Computer Societyen_US
dc.sourceScopus
dc.sourcetitle2013, 7th International Conference on Signal Processing and Communication Systems, ICSPCS 2013 - Proceedings
dc.subjectcoverage
dc.subjectenergy
dc.subjectmulti-objective optimization
dc.subjectsensor node placement
dc.subjectWireless Sensor Network
dc.subjectCommunication systems
dc.subjectEnergy utilization
dc.subjectSensor nodes
dc.subjectSignal processing
dc.subjectWireless sensor networks
dc.subjectBiologically inspired
dc.subjectcoverage
dc.subjectenergy
dc.subjectMinimum energy consumption
dc.subjectObjective functions
dc.subjectOptimization techniques
dc.subjectSensor node placement
dc.subjectTotal energy consumption
dc.subjectMultiobjective optimization
dc.titleMulti-objective Optimization (MOO) approach for sensor node placement in WSNen_US
dc.typeConference paperen_US
dspace.entity.typePublication
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