04386nam 2200625 450 991082455840332120200520144314.01-119-07317-01-119-07315-41-119-07316-2(CKB)3710000000315824(EBL)1890999(SSID)ssj0001431735(PQKBManifestationID)11828048(PQKBTitleCode)TC0001431735(PQKBWorkID)11387406(PQKB)11432555(MiAaPQ)EBC1890999(Au-PeEL)EBL1890999(CaPaEBR)ebr10997837(OCoLC)898213752(PPN)20398739X(EXLCZ)99371000000031582420150106h20152015 uy 0engur|n|---|||||txtccrBandwidth allocation for video under quality of service constraints /Bushra Anjum, Harry PerrosLondon, England ;Hoboken, New Jersey :ISTE :Wiley,2015.©20151 online resource (153 p.)FOCUS Networks and Telecommunication SeriesDescription based upon print version of record.1-84821-746-3 Includes bibliographical references and index.Cover; 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 constraintsI.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. Conclusions2: 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 flows4.4. 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 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 traveFocus series in networks and telecommunications.Data compression (Telecommunication)Data compression (Telecommunication)005.746Anjum Bushra1647315Perros HarryMiAaPQMiAaPQMiAaPQBOOK9910824558403321Bandwidth allocation for video under quality of service constraints3994814UNINA