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dc.contributor.authorAndreou, Panayiotis G.en
dc.contributor.authorZeinalipour-Yazdi, Constantinos D.en
dc.contributor.authorAndreou, Maria I.en
dc.contributor.authorChrysanthis, Panos K.en
dc.contributor.authorSamaras, George S.en
dc.creatorAndreou, Panayiotis G.en
dc.creatorZeinalipour-Yazdi, Constantinos D.en
dc.creatorAndreou, Maria I.en
dc.creatorChrysanthis, Panos K.en
dc.creatorSamaras, George S.en
dc.date.accessioned2019-11-13T10:38:14Z
dc.date.available2019-11-13T10:38:14Z
dc.date.issued2009
dc.identifier.isbn978-0-7695-3650-7
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/53524
dc.description.abstractThis paper assumes a set of n mobile sensors that move in the Euclidean plane as a swarm. Our objectives are to explore a given geographic region by detecting spatio-temporal events of interest and to store these events in the network until the user requests them. Such a setting finds applications in mobile environments where the user (i.e., the sink) is infrequently within communication range from the field deployment. Our framework, coined SenseSwarm, dynamically partitions the sensing devices into perimeter and core nodes. Data acquisition is scheduled at the perimeter, in order to minimize energy consumption, while storage and replication takes place at the core nodes which are physically and logically shielded to threats and obstacles. To efficiently identify the nodes laying on the perimeter of the swarm we devise the Perimeter Algorithm (PA), an efficient distributed algorithm with a low communication complexity. For storage and fault-tolerance we devise the Data Replication Algorithm (DRA), a voting-based replication scheme that enables the exact retrieval of events from the network in cases of failures. Our trace-driven experimentation shows that our framework can offer significant energy reductions while maintaining high data availability rates. In particular, we found that when failures are less than 60% failure then we can recover over 80% of generated events exactly. © 2009 IEEE.en
dc.sourceProceedings - IEEE International Conference on Mobile Data Managementen
dc.source2009 10th International Conference on Mobile Data Management: Systems, Services and Middleware, MDM 2009en
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-70349500525&doi=10.1109%2fMDM.2009.36&partnerID=40&md5=0801f5ceb1e4b36c6318bd7e01d435a3
dc.subjectQuality assuranceen
dc.subjectParallel algorithmsen
dc.subjectWireless networksen
dc.subjectSensor networksen
dc.subjectEnergy consumptionen
dc.subjectFault toleranceen
dc.subjectMobile sensor networksen
dc.subjectElectric load forecastingen
dc.subjectMiddlewareen
dc.subjectMobile environmentsen
dc.subjectEnergy reductionen
dc.subjectCommunication complexityen
dc.subjectCommunication rangeen
dc.subjectCore nodesen
dc.subjectData availabilityen
dc.subjectData replicationen
dc.subjectData replication algorithmen
dc.subjectDistributed algorithmen
dc.subjectEuclidean planesen
dc.subjectField deploymenten
dc.subjectGeographic regionsen
dc.subjectMobile sensorsen
dc.subjectSensing devicesen
dc.subjectSpatio-temporal eventsen
dc.titlePerimeter-based data replication in mobile sensor networksen
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.identifier.doi10.1109/MDM.2009.36
dc.description.startingpage244
dc.description.endingpage251
dc.author.faculty002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Πληροφορικής / Department of Computer Science
dc.type.uhtypeConference Objecten
dc.description.notes<p>Cited By :3</p>en
dc.contributor.orcidZeinalipour-Yazdi, Constantinos D. [0000-0002-8388-1549]
dc.contributor.orcidAndreou, Panayiotis G. [0000-0002-6369-1094]
dc.contributor.orcidChrysanthis, Panos K. [0000-0001-7189-9816]
dc.gnosis.orcid0000-0002-8388-1549
dc.gnosis.orcid0000-0002-6369-1094
dc.gnosis.orcid0000-0001-7189-9816


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