1.

Record Nr.

UNINA9910132307603321

Autore

Anjum Bushra

Titolo

Bandwidth allocation for video under quality of service constraints / / Bushra Anjum, Harry Perros

Pubbl/distr/stampa

London, England ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , 2015

©2015

ISBN

1-119-07317-0

1-119-07315-4

1-119-07316-2

Descrizione fisica

1 online resource (153 p.)

Collana

FOCUS Networks and Telecommunication Series

Disciplina

005.746

Soggetti

Data compression (Telecommunication)

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

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 constraints

I.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

2: 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

4.4. 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

Sommario/riassunto

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