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dc.contributor.authorZeinalipour-Yazdi, Constantinos D.en
dc.contributor.authorAndreou, Panayiotis G.en
dc.contributor.authorChrysanthis, Panos K.en
dc.contributor.authorSamaras, George S.en
dc.creatorZeinalipour-Yazdi, Constantinos D.en
dc.creatorAndreou, Panayiotis G.en
dc.creatorChrysanthis, Panos K.en
dc.creatorSamaras, George S.en
dc.date.accessioned2019-11-13T10:43:02Z
dc.date.available2019-11-13T10:43:02Z
dc.date.issued2007
dc.identifier.isbn978-1-59593-911-1
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/55175
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 and aggregating spatio-temporal events of interest and to store these events in the network until the user requests them. Such a setting finds applications in 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 perimeter of the swarm we devise the Perimeter Algorithm (PA), an efficient distributed algorithm with a message complexity of O(p + n), where p denotes the number of nodes on the perimeter and n the overall number of nodes. For storage and replication we devise a spatio-temporal in-network aggregation scheme based on minimum bounding rectangles and minimum bounding cuboids. Our trace-driven experimentation shows that our framework can offer significant energy reductions while maintaining high data availability rates.en
dc.sourceACM International Conference Proceeding Seriesen
dc.sourceDMSN '07: 4th Workshop on Data Management for Sensor Networksen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-38849091976&doi=10.1145%2f1286380.1286384&partnerID=40&md5=967fc8cfb57d9a0fac0e10df6f778f23
dc.subjectParallel algorithmsen
dc.subjectMobile telecommunication systemsen
dc.subjectWireless sensor networksen
dc.subjectTelecommunication linksen
dc.subjectData acquisitionen
dc.subjectQuery processingen
dc.subjectMobile sensorsen
dc.subjectSensing devicesen
dc.subjectData availability ratesen
dc.subjectPerimeter Algorithm (PA)en
dc.titleSenseSwarm: A perimeter-based data acquisition framework for mobile sensor networksen
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.identifier.doi10.1145/1286380.1286384
dc.description.volume273
dc.description.startingpage13
dc.description.endingpage18
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>Sponsors: Intelen
dc.description.notesConference code: 71378en
dc.description.notesCited By :7</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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