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dc.contributor.authorPark, Sungyun
dc.contributor.authorShin, Kwangcheol
dc.contributor.authorAbraham, Ajith
dc.contributor.authorHan, SangYong
dc.date.accessioned2015-09-30T08:15:50Z
dc.date.accessioned2015-11-18T15:37:53Z
dc.date.available2015-09-30T08:15:50Z
dc.date.available2015-11-18T15:37:53Z
dc.date.issued2007
dc.identifier.citationSensors 2007, 7(5):730-742nb_NO
dc.identifier.issn1424-8220
dc.identifier.urihttp://hdl.handle.net/11250/2364641
dc.description.abstractWireless sensor networks are composed of a huge number of sensor nodes, which have limited resources - energy, memory and computation power. Energies are directly related to the lifetime of sensor network. If sensor nodes can be grouped to clusters, cluster member sensor nodes only need to communicate with cluster center (head) and this leads to energy conservation of the member sensors. So, how to compose clusters with minimal number of cluster heads, while including each node in a cluster is an important research issue. We propose a new advanced optimization algorithm for sensor network clustering. Using the proposed optimization algorithm, redundant cluster heads are eliminated, and unnecessarily overlapped clusters are merged. Optimization algorithm can be used as a clustering algorithm by itself and also manage the dynamic changes like node addition or die-out, while the network is even on the working state. We tested the proposed method as a clustering algorithm and compared it with two other recent sensor network clustering algorithms, Algorithm for Cluster Establishment (ACE) and Self Organizing Sensor network algorithm (SOS). The experiments results not only illustrate that the proposed algorithm could result in clusters with smaller number of cluster heads than others with any density of sensor networks, but also that the performance is more stable, which is also verified through repeated experiments.nb_NO
dc.language.isoengnb_NO
dc.publisherMDPInb_NO
dc.titleOptimized Self Organized Sensor Networksnb_NO
dc.typeJournal articlenb_NO
dc.typePeer revieweden_GB
dc.date.updated2015-09-30T08:15:50Z
dc.source.pagenumber730-742nb_NO
dc.source.volume7nb_NO
dc.source.journalSensorsnb_NO
dc.source.issue5nb_NO
dc.identifier.doi10.3390/s7050730
dc.identifier.cristin371283
dc.description.localcodeThis is an open access article distributed under the Creative Commons Attribution License (CC BY) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.nb_NO


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