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dc.contributor.authorBiswas, Kamanashis
dc.contributor.authorMuthukkumarasamy, Vallipuram
dc.contributor.authorSithirasenan, Elankayer
dc.contributor.editorPalaniswami, M
dc.contributor.editorLeckie, C
dc.contributor.editorKanhere, S
dc.contributor.editorGubbi, J
dc.date.accessioned2017-05-03T14:27:40Z
dc.date.available2017-05-03T14:27:40Z
dc.date.issued2013
dc.date.modified2014-05-15T21:47:30Z
dc.identifier.isbn978-1-4673-5499-8
dc.identifier.refurihttp://www.issnip.org/2013/
dc.identifier.doi10.1109/ISSNIP.2013.6529795
dc.identifier.urihttp://hdl.handle.net/10072/59113
dc.description.abstractIn this paper we present a self-organizing, singlehop clustering scheme, which is based on partitioning sensor networks into several disjoint cliques. Clustering sensor nodes into small groups is an effective method to achieve scalability, fault tolerance, load balancing, routing etc. Here, we develop and analyze maximal clique based cluster-first technique where each node obtains a list of its neighbours' connectivity as well as their degree of connection at first. Then, the node with highest degree of connection initiates clique formation process and makes the cluster. Among all the members of the cluster, the node with maximum energy is selected as cluster head (CH). The proposed technique has a number of advantages. For example, it requires only the knowledge of one-hop neighbours to form clusters. Furthermore, the clustering algorithm is robust for topological change caused by node failure, node mobility, CH change and even for node insertion or removal. Simulation results show that our proposed clustering scheme gives better performance in terms of cluster size, variance of cluster size, and number of single node clusters than the existing clustering algorithms such as Secure Distributed Clustering, LEACH and LCA.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.format.extent108500 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.publisherIEEE
dc.publisher.placeUnited States
dc.publisher.urihttp://www.issnip.org/2013/
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofconferencenameIEEE 8th International Conference on Intelligent Sensors, Sensor Networks and Information Processing (IEEE ISSNIP)
dc.relation.ispartofconferencetitle2013 IEEE EIGHTH INTERNATIONAL CONFERENCE ON INTELLIGENT SENSORS, SENSOR NETWORKS AND INFORMATION PROCESSING
dc.relation.ispartofdatefrom2013-04-02
dc.relation.ispartofdateto2013-04-05
dc.relation.ispartoflocationMelbourne, AUSTRALIA
dc.relation.ispartofpagefrom237
dc.relation.ispartofpagefrom5 pages
dc.relation.ispartofpageto241
dc.relation.ispartofpageto5 pages
dc.relation.ispartofvolume1
dc.rights.retentionY
dc.subject.fieldofresearchOther information and computing sciences not elsewhere classified
dc.subject.fieldofresearchcode469999
dc.titleMaximal clique based clustering scheme for wireless sensor networks
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
gro.facultyGriffith Sciences, School of Information and Communication Technology
gro.rights.copyright© 2013 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
gro.date.issued2013
gro.hasfulltextFull Text
gro.griffith.authorMuthukkumarasamy, Vallipuram


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    Contains papers delivered by Griffith authors at national and international conferences.

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