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dc.contributor.authorAlaybeyoğlu, Ayşegül
dc.contributor.authorDağdeviren, Orhan
dc.contributor.authorErciyeş, Kayhan
dc.contributor.authorKantarcı, Aylin
dc.date.accessioned2016-11-14T08:56:23Z
dc.date.available2016-11-14T08:56:23Z
dc.date.issued2009
dc.identifier.citationAlaybeyoğlu, A., Dağdeviren, O., Erciyeş, K., and Kantarcı, A. (2009, September 14-16). Performance evaluation of cluster-based target tracking protocols for wireless sensor networks. Paper presented at the 24th International Symposium on Computer and Information Sciences, ISCIS 2009. doi:10.1109/ISCIS.2009.5291806en_US
dc.identifier.isbn9781424450237
dc.identifier.urihttp://doi.org/10.1109/ISCIS.2009.5291806
dc.identifier.urihttp://hdl.handle.net/11147/2437
dc.description24th International Symposium on Computer and Information Sciences, ISCIS 2009; Guzelyurt; Cyprus; 14 September 2009 through 16 September 2009en_US
dc.description.abstractTarget tracking is an important application type for wireless sensor networks (WSN). Recently, various approaches [1-11] are proposed to maintain the accurate tracking of the targets as well as low energy consumption. Clustering is a fundamental technique to manage the scarce network resources [12-19]. The message complexity of an application can be significantly decreased when it is redesigned on top of a clustered network. Clustering has provided an efficient infrastructure in many existing studies [1-8]. The clusters can be constructed before the target enters the region which is called the static method [1-4] or clusters are created by using received signal strength (RSS) from target which is called the dynamic method [5-8]. In this paper we provide simulations of static and dynamic clustering algorithms against various mobility models and target speeds. The mobility models that we applied are Random Waypoint Model, Random Direct Model and Gauss Markov Model. We provide metrics to measure the tracking performance of both approaches. We show that the dynamic clustering is favorable in terms of tracking accuracy whereas the energy consumption of static clustering is significantly smaller. We also show that the target moving with Gauss Markov Model can be tracked more accurately than the other models.en_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.relation.isversionof10.1109/ISCIS.2009.5291806en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectTarget trackingen_US
dc.subjectClustering algorithmsen_US
dc.subjectWireless sensor networksen_US
dc.subjectGauss-Markov modelsen_US
dc.subjectNetwork protocolsen_US
dc.titlePerformance evaluation of cluster-based target tracking protocols for wireless sensor networksen_US
dc.typeconferenceObjecten_US
dc.contributor.authorIDTR15997en_US
dc.contributor.institutionauthorDağdeviren, Orhan
dc.relation.journal24th International Symposium on Computer and Information Sciences, ISCIS 2009en_US
dc.contributor.departmentIzmir Institute of Technology. Computer Engineeringen_US
dc.identifier.startpage357en_US
dc.identifier.endpage362en_US
dc.identifier.wosWOS:000275024200063
dc.identifier.scopusSCOPUS:2-s2.0-73949119559
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US


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