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Markov-modulated Bernoulli-based performance analysis for BLUE algorithm under bursty and correlated traffics

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dc.Conferencecode111402
dc.Conferencedate2 September 2014 through 4 September 2014
dc.Conferencename1st International Conference on Computer, Communications, and Control Technology, I4CT 2014
dc.citedby3
dc.contributor.affiliationsFaculty of Science and Technology
dc.contributor.affiliationsUniversiti Sains Islam Malaysia (USIM)
dc.contributor.affiliationsArab Open University
dc.contributor.authorSaaidah A.M.en_US
dc.contributor.authorJali M.Z.en_US
dc.contributor.authorMarhusin M.F.en_US
dc.contributor.authorAbdel-Jaber H.en_US
dc.date.accessioned2024-05-29T01:59:13Z
dc.date.available2024-05-29T01:59:13Z
dc.date.issued2014
dc.description.abstractIn this study, the discrete-time performance of BLUE algorithms under bursty and correlated traffics is analyzed using two-state Markov-modulated Bernoulli arrival process (BLUE-MMBP-2). A two-dimensional discrete-time Markov chain is used to model the BLUE algorithm for two traffic classes, in which each dimension corresponds to a traffic class and the parameters of that traffic class. The MMBP is used to replace the conventional and widely-used Bernoulli process (BP) in evaluating and proposing analytical models based on the BLUE algorithm. The BP captures neither the traffic correlation nor the burstiness. The proposed approach is simulated, and the obtained results are compared with that of the BLUE-BP, which can modulate a single traffic class only. The comparison is performed in terms of mean queue length (mql), average queuing delay (D), throughput, packet loss, and dropping probability (DP). The results show that during congestion, particularly heavy congestion under bursty and correlated traffics, the BLUE-MMBP-2 algorithm provides better mql, D, and DP than the BLUE-BP. � 2014 IEEE.
dc.description.natureFinalen_US
dc.identifier.ArtNo6914136
dc.identifier.doi10.1109/I4CT.2014.6914136
dc.identifier.epage14
dc.identifier.isbn9781480000000
dc.identifier.scopus2-s2.0-84925950107
dc.identifier.spage9
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84925950107&doi=10.1109%2fI4CT.2014.6914136&partnerID=40&md5=4459292cd822be0e97caaa955cf731ce
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/10047
dc.languageEnglish
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofI4CT 2014 - 1st International Conference on Computer, Communications, and Control Technology, Proceedings
dc.sourceScopus
dc.subjectBLUE algorithmen_US
dc.subjectcongestion controlen_US
dc.subjectMarkov-modulated Bernoulli processen_US
dc.subjectperformance evaluationen_US
dc.subjectAlgorithmsen_US
dc.subjectCongestion control (communication)en_US
dc.subjectMarkov processesen_US
dc.subjectQueueing networksen_US
dc.subjectBlue algorithmsen_US
dc.subjectCorrelated trafficen_US
dc.subjectDiscrete time Markov chainsen_US
dc.subjectDropping probabilityen_US
dc.subjectMarkov modulated Bernoulli arrival processen_US
dc.subjectMarkov-modulated bernoulli processen_US
dc.subjectPerformance analysisen_US
dc.subjectperformance evaluationen_US
dc.subjectTraffic congestionen_US
dc.titleMarkov-modulated Bernoulli-based performance analysis for BLUE algorithm under bursty and correlated traffics
dc.typeConference Paperen_US
dspace.entity.typePublication

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