| Summary: | 碩士 === 國立交通大學 === 資訊科學與工程研究所 === 97 === Many popular applications and services currently deployed on Internet are based on the traditional client-server model. As the internet steadily broadens the bandwidth scope, some application services such as VoIP (Voice over Internet Protocol), VoD (Video on Demand), IPTV (Internet Protocol Television) that required high bandwidth are deployed extensively. Although Client-Server model is intuitive and easy for implementation, however, the server will become a potential bottleneck when the number of users grows. It is always difficult for a server to provide the service to a large number of clients at the same time because of high cost and scalability problem. Among these services IPTV needs the largest amount of resources such as bandwidth and storage, and it may suffer shortage of resources when a certain number of users use the system at the same time. To accommodate system resource problem, a popular architecture - Peer-to-Peer (P2P) network for Internet service has been developed in recent decade, more and more IPTV services are deployed based on P2P architecture. In P2P network, data scheduling algorithm has a major effect on the data transfer time between the source and destination. Since every link has a different bandwidth, so how to efficiently use the different bandwidth to reduce the data downloading time so that users can get the data quickly becomes an important issue for designing the P2P scheduling algorithm.
In this thesis, we proposed an efficient source peer selection algorithm which uses probing packets to detect both the available bandwidth and transmission status of all of its partners, and use these statistics to choose the current best source to retrieve data so that the download time can be minimized. Finally, OMNet++ simulation shows that our proposed approach can significantly reduce the downloading time with minimum overhead.
|
|---|
