Quality of Service based Retrieval Strategy for Distributed Video on Demand on Multiple Servers

The recent advances and development of inexpensive computers and high speed networking technology have enabled the Video on Demand (VoD) application to connect to shared-computing servers, replacing the traditional computing environments where each application was having its own dedicated computing hardware. The VoD application enables the viewer to select, from a list of video files, his favorite video file and watch its reproduction at will. Early video on demand applications were based on single video server where video streams are initiated from a single server, then with the increase in the number of the clients who became interested in VoD services, the focus became on Distributed VoD architectures (DVoD) where the context of distribution may be distributed system components, distributed streaming servers, distributed media content etc.The VoD server must handle several issues in order to be able to present a successful service. It has to receive the clients’ requests and analyze them, calculate the necessary resources for each request, and decide whether a request can be admitted or not. Once the request is admitted, the server must schedule the request, retrieve the required video data and send the video data in a timely manner so that the client does not suffer data starvation in his buffer during the video reproduction. So, the overall objective of a VoD service provider is to provide a better Quality of Service (QoS). Some issues related to QoS are-efficient use of bandwidth, providing better throughput etc.One of the important issues is to retrieve the video data from the servers in minimum time and to start the playback of the video at client side with a minimum waiting time. The overall time elapsed in retrieving the video data and starting the playback is known as access time. The thesis presents an efficient retrieval strategy for a distributed VoD environment where the basic objective is to minimize the access time by maintaining the presentation continuity at the client side. We have neglected some of the network parameters which may affect the access time, by assuming a high speed network between the servers and the client. The performance of the strategy has been analyzed and is compared with the referred PAR (Play After Retrieval) strategy. Further, the strategy is also analyzed under availability condition which is a more realistic approach.

[1]  Abdelhakim Hafid,et al.  Some principles for quality of service management , 1997, Distributed Syst. Eng..

[2]  Viktor K. Prasanna,et al.  Fault-tolerant analysis for multiple servers movie retrieval strategy for distributed multimedia applications , 2006, Multimedia Tools and Applications.

[3]  Neil R. Storey,et al.  Safety-critical computer systems , 1996 .

[4]  Premkumar T. Devanbu,et al.  Resource Management , 2000, EDO.

[5]  Hongtao Yu,et al.  An efficient algorithm for the video server selection problem , 2000, Globecom '00 - IEEE. Global Telecommunications Conference. Conference Record (Cat. No.00CH37137).

[6]  Bharadwaj Veeravalli,et al.  Efficient Movie Retrieval Strategies for Movie-on-Demand Multimedia Services on Distributed Networks , 2004, Multimedia Tools and Applications.

[7]  Long Chen,et al.  Multiple-server movie-retrieval strategies for distributed multimedia applications: a play-while-retrieve approach , 2006, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[8]  B. Qazzaz Admission Control and Media Delivery Subsystems for Video on Demand Proxy Server , 2004 .

[9]  Jean-Bernard Stefani,et al.  Open Distributed Processing and Multimedia , 1997 .

[10]  Beng Chin Ooi,et al.  A Replication Strategy for Reducing Wait Time in Video-On-Demand Systems , 2004, Multimedia Tools and Applications.

[11]  Bharadwaj Veeravalli,et al.  Access Time Minimization for Distributed Multimedia Applications , 2000, Multimedia Tools and Applications.

[12]  William H. Tetzlaff,et al.  Disk striping and block replication algorithms for video file servers , 1996, Proceedings of the Third IEEE International Conference on Multimedia Computing and Systems.

[13]  David N. Freeman Access time , 2003 .

[14]  Jan H. M. Korst,et al.  Random duplicate storage strategies for load balancing in multimedia servers , 2000, Inf. Process. Lett..

[15]  David Hutchison,et al.  Quality-of-service architecture: Monitoring and control of multimedia communications , 1997 .

[16]  Chor Ping Low,et al.  An efficient retrieval selection algorithm for video servers with random duplicated assignment storage technique , 2002, Inf. Process. Lett..

[17]  Dimitrios N. Serpanos,et al.  Centralized versus distributed multimedia servers , 2000, IEEE Trans. Circuits Syst. Video Technol..

[18]  Hongtao Yu,et al.  Design issues on video-on-demand resource management , 2000, Proceedings IEEE International Conference on Networks 2000 (ICON 2000). Networking Trends and Challenges in the New Millennium.

[19]  Jari Koistinen,et al.  Worth-based multi-category quality-of-service negotiation in distributed object infrastructures , 1998, Proceedings Second International Enterprise Distributed Object Computing (Cat. No.98EX244).

[20]  Y.-W. Leung,et al.  Assignment of movies to heterogeneous video servers , 2005, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[21]  A. Narasimhan,et al.  Distributed multimedia applications-opportunities, issues, risk and challenges: a closer look , 1997, Proceedings Intelligent Information Systems. IIS'97.

[22]  Frédéric Thiesse,et al.  Constant data length retrieval for video servers with variable bit rate streams , 1996, Proceedings of the Third IEEE International Conference on Multimedia Computing and Systems.

[23]  N. Meyers,et al.  H = W. , 1964, Proceedings of the National Academy of Sciences of the United States of America.

[24]  Klara Nahrstedt,et al.  Resource Management in Networked Multimedia Systems , 1995, Computer.

[25]  Gregor von Bochmann,et al.  Distributed Multimedia and QOS: A Survey , 1995, IEEE Multim..

[26]  James Z. Wang,et al.  Data allocation algorithms for distributed video servers , 2000, MM 2000.

[27]  Andrew T. Campbell,et al.  A survey of QoS architectures , 1998, Multimedia Systems.

[28]  Azman Samsudin,et al.  Data storage and retrieval for video-on-demand servers , 2002, Fourth International Symposium on Multimedia Software Engineering, 2002. Proceedings..