LEADER 04385nam 2200625 450 001 9910132307603321 005 20200520144314.0 010 $a1-119-07317-0 010 $a1-119-07315-4 010 $a1-119-07316-2 035 $a(CKB)3710000000315824 035 $a(EBL)1890999 035 $a(SSID)ssj0001431735 035 $a(PQKBManifestationID)11828048 035 $a(PQKBTitleCode)TC0001431735 035 $a(PQKBWorkID)11387406 035 $a(PQKB)11432555 035 $a(MiAaPQ)EBC1890999 035 $a(Au-PeEL)EBL1890999 035 $a(CaPaEBR)ebr10997837 035 $a(OCoLC)898213752 035 $a(PPN)20398739X 035 $a(EXLCZ)993710000000315824 100 $a20150106h20152015 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aBandwidth allocation for video under quality of service constraints /$fBushra Anjum, Harry Perros 210 1$aLondon, England ;$aHoboken, New Jersey :$cISTE :$cWiley,$d2015. 210 4$dİ2015 215 $a1 online resource (153 p.) 225 1 $aFOCUS Networks and Telecommunication Series 300 $aDescription based upon print version of record. 311 $a1-84821-746-3 320 $aIncludes bibliographical references and index. 327 $aCover; Title Page; Copyright; Contents; Biographies; Bushra Anjum; Harry G. Perros; Acronyms; Introduction; I.1. QoS evolution in the IP network; I.1.1. Real Time Protocol (RTP); I.1.2. Integrated Services (IntServ); I.1.3. Differentiated Services (DiffServ); I.1.4. Multiprotocol Label Switching (MPLS); I.2. Elements of QoS architecture; I.2.1. Traffic classification; I.2.2. Queuing and scheduling policies; I.2.3. Policing of a packet flow; I.2.4. CAC; I.2.5. Traffic engineering; I.3. Problem definition: bandwidth allocation under QoS constraints 327 $aI.3.1. Bandwidth allocation based on the packet loss rate - literature reviewI.3.2. Bandwidth allocation based on end-to-end delay - literature review; I.4. Organization of the book; 1: Partitioning the End-to-End QoS Budget to Domains; 1.1. The need for adding percentiles; 1.2. Calculation of the weight function; 1.2.1. Exponential components with identical rate parameters; 1.2.2. Exponential components with different rate parameters; 1.2.3. Two-stage Coxian; 1.3. Interprovider quality of service; 1.4. Single source shortest path using Dijkstra's algorithm; 1.5. Conclusions 327 $a2: Bandwidth Allocation for Video: MMPP2 Arrivals2.1. The queueing network under study; 2.2. Single-node decomposition; 2.3. Bandwidth estimation based on bounds; 2.4. Validation; 2.5. Conclusions; 3: Bandwidth Allocation for Video: MAP2 Arrivals; 3.1. The queueing network under study; 3.2. End-to-end delay estimation based on bounds; 3.2.1. The interpolation function; 3.3. Validation; 3.4. Video traces; 3.5. Conclusions; 4: Bandwidth Allocation for Video: Video Traces; 4.1. The proposed algorithm; 4.2. Test traces; 4.3. Bandwidth requirements for homogeneous flows 327 $a4.4. Bandwidth allocation under percentile delay and jitter constraints4.5. Bandwidth allocation under percentile delay, average jitter and packet loss rate constraints; 4.6. Conclusions; Bibliography; Index 330 $a We present queueing-based algorithms to calculate the bandwidth required for a video stream so that the three main Quality of Service constraints, i.e., end-to-end delay, jitter and packet loss, are ensured. Conversational and streaming video-based applications are becoming a major part of the everyday Internet usage. The quality of these applications (QoS), as experienced by the user, depends on three main metrics of the underlying network, namely, end-to-end delay, jitter and packet loss. These metrics are, in turn, directly related to the capacity of the links that the video traffic trave 410 0$aFocus series in networks and telecommunications. 606 $aData compression (Telecommunication) 615 0$aData compression (Telecommunication) 676 $a005.746 700 $aAnjum$b Bushra$0954018 702 $aPerros$b Harry 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910132307603321 996 $aBandwidth allocation for video under quality of service constraints$92157519 997 $aUNINA