SCALABLE VIDEO ON DEMAND - ADAPTIVE INTERNET-BASED DISTRIBUTION可升级的因特网视频按需系统

出版日期:2005-10
ISBN:9780470022689
作者:Zink, Michael
页数:290页

书籍目录

List of FiguresList of TablesAbout the AuthorAcknowledgementsAcronyms1 Introduction 1.1  Why Scalable Internet Video on Demand Systems? 1.2  What is the Goal of this Book? 1.3  Outline of this Book 1.4  Who is this Book for?2 Scalable Adaptive Streaming Architecture 2.1  Distributed Systems 2.2  Replication  2.2.1  Server-initiated Replication  2.2.2  Client-initiated Caching 2.3  Video Distribution System Terminology  2.3.1  Origin Server  2.3.2  Proxy Cache  2.3.3  Cache Replacement  2.3.4 Client  2.3.5  Logical Overlay  2.3.6  Video Object  2.3.7  Video on Demand (VoD)  2.4  Architecture  2.4.1  A Snapshot of Today's Internet Infrastructure  2.4.2  Advantages of Caching  2.4.3  VoD without Scalable Adaptive Streaming  2.4.4  System Scalability  2.4.5  Content Scalability  2.4.6  Combining System and Content Scalability  2.4.7  VoD with Scalable Adaptive Streaming Support 2.5  Scenario for Scalable Adaptive Streaming 2.6  An Example Application for Scalable Adaptive Streaming3 Towards a Scalable Adaptive Streaming Architecture 3.1  Products 3.2  Standardization  3.2.1  IETF  3.2.2  DVB and DAVIC 3.3  Content Scalability-Scalable Encoded Video  3.3.1  Hierarchically Layer-encoded Video  3.3.2  Fine Granularity Scalability  3.3.3  Multiple Description Coding  3.3.4  Comparison of Layered Encoding Approaches 3.4  Congestion Control-TCP-friendliness  3.4.1  The Window-based Approach  3.4.2  The Rate-based Approach 3.5  Adaptive Streaming-Streaming Layer-encoded Video without Caches 3.6  System Scalability-Caches  3.6.1  Partial Caching of Video Objects  3.6.2  Time-based Partial Caching  3.6.3  Bandwidth-based Partial Caching  3.6.4  Disadvantages of Partial Video Caching 3.7  Reliable Transport into Caches 3.8  Cache Clusters4 Quality Variations in Layer-encoded Video 4.1  What is the Relation between Objective and Subjective Quality? 4.2  Quality Metrics for Video  4.2.1  Existing Work on Quality Metrics for Layer-encoded Video  4.2.2  Objective Video Quality Assessment 4.3  Test Environment  4.3.1  Layer-encoded Video Format-SPEG  4.3.2  Test Generation-Full Control  4.3.3  Measurement Method-Stimulus Comparison  4.3.4  Test Application-Enforcing Time Constraints 4.4  Experiment  4.4.1  Scenario  4.4.2  Candidates  ……5 Retrabsnussion Scheduling6  Polishing7  Fair Share Claiming8  Scalable TCP-friendly Video Distribution for Heterogeneous Clients9  Improved Video Distribution in Today's InternetAppendix A:LC-RTP(Loss Collection RTP)Appendix B:Preliminary Subjective AssessmentAppendix C:A Toolkit for Dynamically Reconfigurable Multimedia Distribution SystemsReferencesIndex

作者简介

In recent years, the proliferation of available video content and the popularity of the Internet have encouraged service providers to develop new ways of distributing content to clients. Increasing video scaling ratios and advanced digital signal processing techniques have led to Internet Video-on-Demand applications, but these currently lack efficiency and quality. Scalable Video on Demand: Adaptive Internet-based Distribution examines how current video compression and streaming can be used to deliver high-quality applications over the Internet. In addition to analysing the problems of client heterogeneity and the absence of Quality of Service in the Internet, this book: assesses existing products and encoding formats; presents new algorithms and protocols for optimised on-line video streaming architectures; includes real-world application examples and experiments; sets out a practical ‘toolkit’ for Dynamically Reconfigurable Multimedia Distribution Systems. Written by an expert in the field of video distribution, Scalable Video on Demand: Adaptive Internet-based Distribution provides a novel approach to the design and implementation of Video-on-Demand systems for Software Engineers and researchers. It will also be useful for graduate students following Electronic Engineering and Computer Science courses.


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