Show simple item record

dc.contributor.authorAntoniou, Pavlos Ch.en
dc.contributor.authorPitsillides, Andreasen
dc.contributor.authorEngelbrecht, A.en
dc.contributor.authorBlackwell, T.en
dc.contributor.authorMichael, Loizosen
dc.creatorAntoniou, Pavlosen
dc.creatorPitsillides, Andreasen
dc.creatorEngelbrecht, A.en
dc.creatorBlackwell, T.en
dc.creatorMichael, Loizosen
dc.date.accessioned2019-11-13T10:38:20Z
dc.date.available2019-11-13T10:38:20Z
dc.date.issued2011
dc.identifier.isbn978-1-4503-0913-4
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/53567
dc.description.abstractRecently, sensor networks have attracted significant research interest. However, most studies have mainly focused on protocols for applications in which network performance assurances are not considered essential. With the emergence of mission-critical applications, performance control mechanisms are considered of prime importance. Performance control can be carried out by robust congestion control approaches that aim to keep the network operational under varying network conditions. Swarm intelligence is successfully employed to combat congestion by mimicking the collective behavior of bird flocks. In this way, the emerging global behavior of minimum congestion is achieved collectively. A flock-based congestion control (Flock-CC) approach was proposed in the past. This paper presents a new, simpler Flock-CC approach. Performance evaluations focus on parameter setting and on comparative studies between the new and the earlier version of Flock-CC. © 2011 ACM.en
dc.sourceACM International Conference Proceeding Seriesen
dc.source4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL'11en
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84856692723&doi=10.1145%2f2093698.2093776&partnerID=40&md5=d470dfffdc6c3e0a6bcb670a02dc912f
dc.subjectArtificial intelligenceen
dc.subjectCommunicationen
dc.subjectMission critical applicationsen
dc.subjectComparative studiesen
dc.subjectCongestion control (communication)en
dc.subjectNetwork performanceen
dc.subjectPerformance evaluationen
dc.subjectBird flocksen
dc.subjectCollective behavioren
dc.subjectCellular automataen
dc.subjectGlobal behaviorsen
dc.subjectNetwork conditionen
dc.subjectParameter settingen
dc.subjectPerformance controlen
dc.subjectSwarm Intelligenceen
dc.titleApplying swarm intelligence to a novel congestion control approach for wireless sensor networksen
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.identifier.doi10.1145/2093698.2093776
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: Kyranova Ltd, Center for TeleInFrastruktur (CTIF)en
dc.description.notesIEEEen
dc.description.notesUniversitat Pompeu Fabraen
dc.description.notesTechnical University of Catalonia (UPC)en
dc.description.notesRiver Publishersen
dc.description.notesTechnological Center for Telecommunications of Catalonia (CTTC)en
dc.description.notesConference code: 88372</p>en
dc.contributor.orcidPitsillides, Andreas [0000-0001-5072-2851]
dc.gnosis.orcid0000-0001-5072-2851


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record