Design of Algorithms and Protocols for Peer-To-Peer Streaming Systems

Peer-to-Peer Streaming (P2P-TV) systems have been studied in the literature for some time and they are becoming popular among users as well. P2P-TV systems target the real time delivery of a video stream, therefore posing different challenges compared to more traditional peer-to-peer applications such as file sharing (BitTor-rent) or VoIP (Skype). This document focuses on mesh based P2P-TV systems in which the peers form a generic overlay topology at application level upon which peers exchange small “chunks” of video. In particular, we study two problems related with this kind of systems: i) how to induce peers to share their available resources – such as their available upload bandwidth – in a totally automatic and distributed way; ii) how to localize P2P-TV traffic in order to lower the load on the underlying transport network without impairing the quality of experience (QoE) perceived by users. Goal i) can be achieved playing on two key aspects of P2P-TV systems that are: • the design of the trading phase needed to exchange chunks among neighbors; • the strategy adopted by peers to choose the neighbors to connect with, i.e., the policy employed to build and maintain the overlay topology at application level. The former task has been successfully accomplished with the development of algorithms that aim at adapting the rate at which peers offer chunks to their neighbors to both peer’s available upload bandwidth and to the system demand. The results presented in this document show that the automatic adjustment of transmission rate to available upload capacity reduce delivery delays of chunks, thus improving the experience of users. Focusing on the latter problem, we prove that the topological properties of the overlay have a deep effect on both users’ QoE and network impact. We developed a smart, flexible and fully distributed algorithm for neighbors selection and implemented it in a real P2P-TV client. This let us compare several different strategies for overlay construction in a large campaign of test-bed experiments. Results show that we can actually achieve the goal of leading peers to efficiently share their available resources – goal i) – while keeping a good degree of traffic localization, hence lowering the load on the underlying network – goal ii). Furthermore, our experimental results show that a proper selection of the neighborhood leads to a win-win situation where the performance of the application and QoE are both improved, while the network stress is nicely reduced.