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dc.contributor.authorAntoniou, Pavlos Ch.en
dc.contributor.authorPitsillides, Andreasen
dc.creatorAntoniou, Pavlosen
dc.creatorPitsillides, Andreasen
dc.date.accessioned2019-11-13T10:38:19Z
dc.date.available2019-11-13T10:38:19Z
dc.date.issued2010
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/53562
dc.description.abstractIn the new era of Ambient Intelligence, wireless sensor networks (WSNs) are seen to bridge the gap between physical world and the Internet, making a large amount of information accessible anywhere, anytime. Over the last few years, WSNs are being developed towards a large number of multimedia streaming applications, e.g. video surveillance, traffic control systems, health monitoring, and industrial process control. WSNs consist of small sensor devices (nodes) that are capable of working unattended, without centralized control, under dynamically changing conditions. However, these devices face important limitations in terms of energy, memory and computational power. The uncontrolled use of limited resources in conjunction with the unpredictable nature of WSNs in terms of traffic load injection, wireless link capacity fluctuations and topology modifications may lead to congestion. Congestion can cause increased packet loss and delay. This paper proposes a bio-inspired congestion control approach for WSNs streaming applications that necessitate controlled performance with graceful degradation. In the proposed approach, congestion in WSNs is prevented (or at least minimized) by regulating the rate of each traffic flow based on the Lotka-Volterra competition model. Performance evaluations reveal that the proposed approach achieves adaptability to changing traffic loads, scalability and fairness among flows, while providing graceful performance degradation as the offered load increases. © 2010 Elsevier B.V. All rights reserved.en
dc.sourceComputer Communicationsen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-77957109247&doi=10.1016%2fj.comcom.2010.07.020&partnerID=40&md5=ec8e87563b7d79442270725ddbee13cc
dc.subjectCompetitionen
dc.subjectBio-inspireden
dc.subjectCentralized controlen
dc.subjectSensor networksen
dc.subjectWireless sensor networksen
dc.subjectAmount of informationen
dc.subjectWireless sensoren
dc.subjectDegradationen
dc.subjectTraffic flowen
dc.subjectTraffic surveysen
dc.subjectTraffic congestionen
dc.subjectLotka-Volterraen
dc.subjectSecurity systemsen
dc.subjectSensor deviceen
dc.subjectAmbient intelligenceen
dc.subjectBio-inspired approachen
dc.subjectComputational poweren
dc.subjectCongestion Controlen
dc.subjectCongestion control (CC)en
dc.subjectGraceful degradationen
dc.subjectGraceful performance degradationsen
dc.subjectHealth monitoringen
dc.subjectIndustrial process controlen
dc.subjectLotka-Volterra (LV) competition modelen
dc.subjectLotka-Volterra competition modelen
dc.subjectMultimedia streaming applicationsen
dc.subjectPerformance evaluationen
dc.subjectPhysical worlden
dc.subjectStreaming applicationsen
dc.subjectTraffic loadsen
dc.subjectVideo surveillanceen
dc.subjectWireless linken
dc.subjectWireless sensor networks (WSNs)en
dc.titleA bio-inspired approach for streaming applications in wireless sensor networks based on the Lotka-Volterra competition modelen
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.1016/j.comcom.2010.07.020
dc.description.volume33
dc.description.issue17
dc.description.startingpage2039
dc.description.endingpage2047
dc.author.faculty002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Πληροφορικής / Department of Computer Science
dc.type.uhtypeArticleen
dc.description.notes<p>Cited By :20</p>en
dc.source.abbreviationComput.Commun.en
dc.contributor.orcidPitsillides, Andreas [0000-0001-5072-2851]


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