Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICCW.2010.5503895
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dc.titleA robust harmony search algorithm based clustering protocol for wireless sensor networks
dc.contributor.authorHoang, D.C.
dc.contributor.authorYadav, P.
dc.contributor.authorKumar, R.
dc.contributor.authorPanda, S.K.
dc.date.accessioned2014-06-19T02:56:14Z
dc.date.available2014-06-19T02:56:14Z
dc.date.issued2010
dc.identifier.citationHoang, D.C.,Yadav, P.,Kumar, R.,Panda, S.K. (2010). A robust harmony search algorithm based clustering protocol for wireless sensor networks. 2010 IEEE International Conference on Communications Workshops, ICC 2010 : -. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/ICCW.2010.5503895" target="_blank">https://doi.org/10.1109/ICCW.2010.5503895</a>
dc.identifier.isbn9781424468263
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/69046
dc.description.abstractOptimizing energy consumption is the main concern for designing and planning the operation of the Wireless Sensor Networks (WSNs). Clustering technique is one of the methods utilized to extend lifetime of the network by applying data aggregation and balancing energy consumption among sensor nodes of the network. In this paper, we propose the recently developed, Harmony Search Algorithm (HSA) for minimizing the intra-cluster distance and optimizing the energy consumption of the network. HSA is music based metaheuristic optimization method which is analogous with the music improvisation process where musician continue to polish the pitches in order to obtain better harmony. A comparison is made with the well known cluster-based protocol approach developed for WSNs known as Low-Energy Adaptive Clustering Hierarchy (LEACH), heuristic optimization algorithms like Particle Swarm Optimization (PSO) and Genetic Algorithm(GA) as well as the traditional K-means and Fuzzy C-Means (FCM) clustering algorithms. Simulation results demonstrate that the proposed protocol using HSA can reduce energy consumption and improve the network lifetime. ©2010 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/ICCW.2010.5503895
dc.sourceScopus
dc.subjectClustering
dc.subjectFuzzy C-means
dc.subjectGenetic algorithm(GA)
dc.subjectHarmony search (HS)
dc.subjectHierarchical routing
dc.subjectMeta-heuristic
dc.subjectParticle swarm optimization (PSO)
dc.subjectWireless sensor networks
dc.typeConference Paper
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1109/ICCW.2010.5503895
dc.description.sourcetitle2010 IEEE International Conference on Communications Workshops, ICC 2010
dc.description.page-
dc.identifier.isiutNOT_IN_WOS
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