Quality assurance of streaming data dissemination over p2p network

• Main Authors: Chiu, Wei Chung, 邱威中
• Other Authors: Lien, Yao Nan
• Format: Others
• Language: en_US
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/52884648867925914992

碩士 === 國立政治大學 === 資訊科學學系 === 98 === Numerous new network services arise with the advanced development of network technologies, such as real-time multimedia streaming services. But challenges to network environment come along with the enormous traffic of data flows and rigorous restriction to transmission delay of real-time multimedia streaming services. Under this circumstance, conventional server-client topology suffers from serious packet loss and packet delay due to the overload of servers and their accessing links. Also, extra transmission delay may make packets fail to meet the requirement of real-timed services. Peer-to-peer network is more scalable than server-client model, and is much more tolerable to the transmission errors caused by node or link failures. More importantly, it effectively distributes load from the server to peers. As a consequence, peer-to-peer service architecture becomes very popular for real-time multimedia streaming services recently. Peer-to-peer networks are mostly formed in random fashion. As the size of network grows, packets may have to travel through numerous links to reach far-end receivers. The quality of data may be damaged by insufficient bandwidth of links. For real-time multimedia services, it is not acceptable to users if the cumulated packet delay exceeds a tolerable limit. Our research is trying to find a better topology to transmit multimedia data flows which makes the cumulated delay of the most-far-end user be tolerable and the damage of data quality is minimized. The problem is modeled as a MLDST problem, which is a NP-Complete problem. To solve the problem, we modified Dijkstra’s single-source shortest-path algorithm by bounding the node degree and adding delay constraint. The experiments were carried out on real network environment through PlanetLab. Experiments show that our algorithm outperforms traditional MST and shortest path spanning tree.