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The existing TCP flow completion time distributions are calculated from complicated models, and they are only suitable for short TCP flows. This paper is motivated to build a simple model to derive TCP flow completion time distribution that is suitable for both short and long TCP flows. To build such a model, the distribution of the packet transmission latency under TCP congestion control is firstly calculated. The packet transmission latency is the time needed to successfully deliver a packet, including the time for retransmissions due to packet losses. Semi-Markov process is used to model the TCP congestion window evolution. Using the packet transmission latency distribution together with the TCP congestion window size information, a new parallel queueing model which describes how a file is transmitted by a TCP flow is formed. In the parallel queueing model, the flow completion time distribution is derived, and simulation results from NS2 demonstrate the accuracy of the proposed analysis.", "subjects" : [ { "otype" : "Classification", "mtid" : 10034, "link" : "/api/classification/10034", "label" : "Számítás- és információtudomány", "published" : true, "snippet" : true }, { "otype" : "Classification", "mtid" : 10880, "link" : "/api/classification/10880", "label" : "Villamosmérnöki és informatikai tudományok", "published" : true, "snippet" : true } ], "keywords" : [ { "otype" : "Keyword", "mtid" : 1025943, "link" : "/api/keyword/1025943", "label" : "TCP", "published" : true, "oldId" : 1025943, "snippet" : true }, { "otype" : "Keyword", "mtid" : 1179402, "link" : "/api/keyword/1179402", "label" : "Packet loss", "published" : true, "oldId" : 1179402, "snippet" : true }, { "otype" : "Keyword", "mtid" : 1390080, "link" : "/api/keyword/1390080", "label" : "CONGESTION CONTROL", "published" : true, "oldId" : 1390080, "snippet" : true }, { "otype" : "Keyword", "mtid" : 1892421, "link" : "/api/keyword/1892421", "label" : "flow completion time", "published" : true, "snippet" : true }, { "otype" : "Keyword", "mtid" : 1892422, "link" : "/api/keyword/1892422", "label" : "packet transmission latency", "published" : true, "snippet" : true } ], "digital" : null, "printed" : null, "sourceYear" : 2020, "foreignEdition" : true, "foreignLanguage" : true, "fullPublication" : true, "conferencePublication" : false, "nationalOrigin" : null, "missingAuthor" : false, "oaType" : "NONE", "oaCheckDate" : "2020-05-01", "oaFree" : false, "citationCount" : 0, "citationCountUnpublished" : 0, "citationCountWoOther" : 0, "independentCitCountWoOther" : 0, "doiCitationCount" : 0, "wosCitationCount" : 0, "scopusCitationCount" : 0, "independentCitationCount" : 0, "unhandledCitationCount" : 0, "citingPubCount" : 0, "independentCitingPubCount" : 0, "unhandledCitingPubCount" : 0, "citedPubCount" : 1, "citedCount" : 1, "ratings" : [ { "otype" : "SjrRating", "mtid" : 10769559, "link" : "/api/sjrrating/10769559", "label" : "sjr:Q2 (2019) Scopus - Computer Networks and Communications JOURNAL OF COMMUNICATIONS AND NETWORKS 1229-2370", "listPos" : 98, "rankValue" : 0.49, "type" : "journal", "ratingType" : { "otype" : "RatingType", "mtid" : 10002, "link" : "/api/ratingtype/10002", "label" : "sjr", "code" : "sjr", "published" : true, "snippet" : true }, "subject" : { "otype" : "ClassificationExternal", "mtid" : 1705, "link" : "/api/classificationexternal/1705", "label" : "Scopus - Computer Networks and Communications", "published" : true, "oldId" : 1705, "snippet" : true }, "ranking" : "Q2", "calculation" : "FROM_LAST_YEAR", "published" : true, "snippet" : true } ], "ratingsForSort" : "Q2", "hasCitationDuplums" : false, "directInstitutesForSort" : "", "ownerAuthorCount" : 1, "ownerInstituteCount" : 3, "directInstituteCount" : 0, "authorCount" : 1, "contributorCount" : 0, "hasQualityFactor" : true, "link" : "/api/publication/31059262", "label" : "Luan Gan. 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