P2P Live Video Streaming

University dissertation from Stockholm : KTH Royal Institute of Technology

Abstract: The ever increasing demand for video content directed the focus of researchfrom traditional server-based schemes to peer-to-peer systems for videodelivery. In such systems, video data is delivered to the users by utilizing theresources of the users themselves, leading to a potentially scalable solution.Users connect to each other, forming a p2p overlay network on top of theInternet and exchange the video segments among themselves. The performanceof a p2p system is characterized by its capability to deliver the videocontent to all peers without errors and with the smallest possible delay. Thisconstitutes a challenge since peers dynamically join and leave the overlay andalso contribute different amounts of resources to the system.The contribution of this thesis lies in two areas. The first area is theperformance evaluation of the most prominent p2p streaming architectures.We study the streaming quality in multiple-tree-based systems. We derivemodels to evaluate the stability of a multiple tree overlay in dynamic scenariosand the efficiency of the data distribution over the multiple trees. Then, westudy the data propagation in mesh-based overlays. We develop a generalframework for the evaluation of forwarding algorithms in such overlays anduse this framework to evaluate the performance of four different algorithms.The second area of the thesis is a study of streaming in heterogeneous p2poverlays. The streaming quality depends on the aggregate resources that peerscontribute to the system: low average contribution leads to low streamingquality. Therefore, maintaining high streaming quality requires mechanismsthat either prohibit non-contributing peers or encourage contribution. In thisthesis we investigate both approaches. For the former, we derive a model tocapture the evolution of available capacity in an overlay and propose simpleadmission control mechanisms to avoid capacity drainage. For the latter, inour last work, we propose a novel incentive mechanism that maximizes thestreaming quality in an overlay by encouraging highly contributing peers tooffer more of their resources.

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