| The Peer-to-Peer (P2P) network based P2P streaming technique migrates the multicast functionality from network layer to application layer, which makes full use of network and computing resources of all joined peers to extend system scale, has become a hot topic in streaming technique field recently. The data-driven P2P streaming models based on self-orgnazation topology is one kind of main models recently, which have attracted more attention because of its simple topology protocol, and being resilient to network dynamics. Usually the QoS (Quality of Service) improvements play important roles in current research in such P2P streaming systems. So according to the characteristic of buffered data, we focus on some key problems as following:Taking the characteristic of buffered data into account for partnership maintaining, the synchronization estimation based membership management (SEBMM) mechanism is proposed. The SEBMM considered both the network performance and data synchronization among peers on peer selections, well decreases the probability of data mismatch which is introduced by partially considered of the network performance without considering the data synchronization. Further research shows that the peers running SEBMM scheme will fall short of data receiving because of the selection criterion adopted by SEBMM. Hence, we can improve SEBMM in such approaches as: applying the cache series intersection ratio between peers as synchronization indicator, and taking data mutually complementarity into account when selecting active peers, through which it can increase the data transmission gross. The simulation results demonstrate the feasibility and effectiveness of this solution.An adaptive dynamic data scheduling (ADDS) algorithm is introduced, which determines data assignment according to the states of peers in dynamic and data characters for decoding. The ADDS algorithm defines scheduling performance as a function of task overload and data arriving ratio, and assigns the packets to peers with the best scheduling performance. The aim laying behind is to increase the data arriving rate in time. In order to assure the receiver-end of playback quality, all data packets to be scheduled will be sorted in order by scheduling value firstly before assignment and those packets which are in urgency and important for streaming decoding will be given priority to be transmitted. With the inherent PULL strategy, a controlled PUSH strategy based PUSH-ADDS algorithm is adopted at source-end, which will push some packets to receiver forwardly. PUSS-ADDS can make use of spare bandwidth of active peers.The proposed media object validity prediction based cache management (MOVPCM) manages cached media objects differently according to their caching value to decrease the decoding distortion arising from packet replacement and increase cache hit rate. A multi-source cache management model with the aim of increasing the valid data gross is also proposed, and after relaxed and localized, it is adopted to work out the optimized replacement series by greedy method. MOVPCM makes use of the predicted validity, decoding value and caching cost as factors to calculate the priority for object caching, based on which objects with high decoding value and request probability will have longer life time in cache. Analysis and simulation results show the validity of the MOVPCM method.P2P streaming system is a combination of some key modals involved. Because previous system tends to adopt fasten coupled system, and such systems can't be extended facility, and it mismatches with the loosely coupled P2P environment. So, the prototype system proposed in this thesis adopts a kind of semantic method to achieve peers and streaming data management uniformly through a loosely coupled system construction style, improves the flexibility and expansibility of the system in a certain extent.
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