A key issue in Peer-to-Peer (P2P) live streaming systems is that several participant peers tend to leave within a short time period. For example, such a phenomenon is common at the half time of football games and at the end of the performance of famous artists. Such selfish behavior of the participants causes several problems in P2P networks such as the disconnection of the overlay, the departure of backup peers and the occurrence of cyclic reference to backup peers. In this paper, we propose several techniques for tree-structured P2P live streaming systems to enhance their resilience to the simultaneous departure of some participants. As the baseline of the discussion, we will focus on mTreebone which is a typical churn-resilient P2P live streaming system based on the notion of peer stability. The performance of the proposed techniques is evaluated by simulation. The simulation result indicates that even under high churn rates, the proposed techniques significantly reduce the number of attempts needed to connect to backup peers and the recovery time after a fail.

Most large-scale Peer-to-Peer (P2P) live streaming systems are constructed as a mesh structure, which can provide robustness in the dynamic P2P environment. The pull scheduling algorithm is widely used in this mesh structure, which degrades the performance of the entire system. Recently, network coding was introduced in mesh P2P streaming systems to improve the performance, which makes the push strategy feasible. One of the most famous scheduling algorithms based on network coding is R2, with a random push strategy. Although R2 has achieved some success, the push scheduling strategy still lacks a theoretical model and optimal solution. In this paper, we propose a novel optimal pull-push scheduling algorithm based on network coding, which consists of two stages: the initial pull stage and the push stage. The main contributions of this paper are: 1) we put forward a theoretical analysis model that considers the scarcity and timeliness of segments; 2) we formulate the push scheduling problem to be a global optimization problem and decompose it into local optimization problems on individual peers; 3) we introduce some rules to transform the local optimization problem into a classical min-cost optimization problem for solving it; 4) We combine the pull strategy with the push strategy and systematically realize our scheduling algorithm. Simulation results demonstrate that decode delay, decode ratio and redundant fraction of the P2P streaming system with our algorithm can be significantly improved, without losing throughput and increasing overhead.