Peer-to-Peer Video Conferencing Using Hybrid Content Distribution Model | Science Publications

Journal of Computer Science

Ali Shanoon¹  Imad Jasim¹  Alhamza Munther¹  Salah Noori¹  Ayad Hussain¹  Azlan Osman¹ 

关键词: Peer-to-peer;    content distribution;    heterogeneous network;    widespread applications;    video conferencing system;   

DOI  :  10.3844/jcssp.2012.1134.1142

学科分类：计算机科学（综合）

来源: Science Publications

【 摘 要 】

Problem statement: Multimedia Conferencing System (MCS) is a server-based video conferencing system. One of the most critical limitations faced by this approach is the scalability issue. In the MCS, the outgoing bandwidth of the server is shared among all concurrent clients. Thus, the more clients there are, the lesser the bandwidth each client can have. The performance of this approach therefore deteriorates rapidly as the number of simultaneous clients increases. In addition, a pure server-based solution is expensive. Approach: In this research, the server-based infrastructure is modified into a peer-to-peer video conferencing system while preserving the same functionality and features of the existing MCS. This modification can be achieved using a hybrid content distribution model, which is a combination of fluid and chunk content distribution models to distribute parts of the video stream fairly among participants. The hybrid content distribution model offers a better way of handling heterogeneous networks because it can distinguish between a fast peer and a slow peer, dealing with each one according to its capabilities. Results: In our proposed system, the function server will not be used for video distribution. Instead, it will only be used for monitoring and controlling the peers to reduce the burden on the servers. Experimental results conducted in the nation advanced IPv6 center as a real environment and live conferencing. Conclusion: This will lead to overcome the problem of scalability and a bandwidth bottleneck on the main server and achieve good way to distribute video chunks.

【 授权许可】

Unknown