Peer-to-peer streaming has emerged as a killer application in today's Internet, delivering a large variety of live multimedia content to millions of users at any given time with low server cost. Though successfully deployed, the efficiency and optimality of the current peer-to-peer streaming protocols are still less than satisfactory. In this thesis, we investigate optimizing solutions to enhance the performance of the state-of-the-art mesh-based peer-to-peer streaming systems, utilizing both theoretical performance modeling and extensive real-world measurements. First, we model peer-to-peer streaming applications in both the single-overlay and multi-overlay scenarios, based on the solid foundation of optimization and game theories. Using these models, we design efficient and fully decentralized solutions to achieve performance optimization in peer-to-peer streaming. Then, based on a large volume of live measurements from a commercial large-scale peer-to-peer streaming application, we extensively study the real-world performance of peer-to-peer streaming over a long period of time. Highlights of our measurement study include the topological characterization of large-scale streaming meshes, the statistical characterization of inter-peer bandwidth availability, and the investigation of server capacity utilization in peer-to-peer streaming. Utilizing in-depth insights from our measurements, we design practical algorithms that advance the performance of key protocols in peer-to-peer live streaming. We show that our optimizing solutions fulfill their design objectives in various realistic scenarios, using extensive simulations and experiments.

Peer-to-peer streaming has emerged as a killer application in today's Internet, delivering a large variety of live multimedia content to millions of users at any given time with low server cost. Though successfully deployed, the efficiency and optimality of the current peer-to-peer streaming protocols are still less than satisfactory. In this thesis, we investigate optimizing solutions to enhance the performance of the state-of-the-art mesh-based peer-to-peer streaming systems, utilizing both theoretical performance modeling and extensive real-world measurements. First, we model peer-to-peer streaming applications in both the single-overlay and multi-overlay scenarios, based on the solid foundation of optimization and game theories. Using these models, we design efficient and fully decentralized solutions to achieve performance optimization in peer-to-peer streaming. Then, based on a large volume of live measurements from a commercial large-scale peer-to-peer streaming application, we extensively study the real-world performance of peer-to-peer streaming over a long period of time. Highlights of our measurement study include the topological characterization of large-scale streaming meshes, the statistical characterization of inter-peer bandwidth availability, and the investigation of server capacity utilization in peer-to-peer streaming. Utilizing in-depth insights from our measurements, we design practical algorithms that advance the performance of key protocols in peer-to-peer live streaming. We show that our optimizing solutions fulfill their design objectives in various realistic scenarios, using extensive simulations and experiments.

Peer-to-peer (P2P) streaming has recently received much research attention, with successful commercial systems showing its viability in the Internet. Despite the remarkable popularity in real-world systems, the fundamental properties and limitations are not yet well understood from a theoretical perspective, as there exists a significant gap between the fundamental limits and the performance achieved in practice. In this thesis, we seek to provide an in-depth analytical understanding of fundamental properties and limitations of P2P streaming systems, with a particular spotlight on the performance gap. We first identify the major problem in existing streaming protocols and show that this problem accounts for most of the gap separating the actual and optimal performances of the streaming systems. We then propose a remedy based on network coding to address this problem and show that the gap to the fundamental limits can be significantly reduced.

Peer-to-peer (P2P) streaming has recently received much research attention, with successful commercial systems showing its viability in the Internet. Despite the remarkable popularity in real-world systems, the fundamental properties and limitations are not yet well understood from a theoretical perspective, as there exists a significant gap between the fundamental limits and the performance achieved in practice. In this thesis, we seek to provide an in-depth analytical understanding of fundamental properties and limitations of P2P streaming systems, with a particular spotlight on the performance gap. We first identify the major problem in existing streaming protocols and show that this problem accounts for most of the gap separating the actual and optimal performances of the streaming systems. We then propose a remedy based on network coding to address this problem and show that the gap to the fundamental limits can be significantly reduced.