Master of Sciences, Case Western Reserve University, 2010, EECS - Computer and Information Sciences

Live streaming applications, especially those based on peer-to-peer networks, are becoming popular nowadays. It is widely known that there are still some performance challenges on transmission and scalability in peer-to-peer live streaming system. This thesis focuses on improving transmission efficiency in live media streaming and improving scalability in peer-to-peer live streaming systems. First, we improve transmission efficiency in live media streaming by studying chunk scheduling algorithms which include Greedy, Rarest First, Mixed, Random and our proposed Alternate algorithms, and delivery methods which include Push and Pull methods. Based on the evaluation of startup latency and streaming continuity for different chunk scheduling algorithms and delivery methods, we discuss how to make an optimal choice for better transmission efficiency. Second, we improve the scalability for peer-to-peer live streaming system by utilizing our incentive model, a bank incentive model, which can encourage peers to make more contribution in order to obtain extra benefits from their neighbors and the system. As well as applying encouragement to the peers, our incentive model can support multiple platforms and the extensibility of incentive strategies.

Committee: Shudong Jin (Committee Chair); Michael Rabinovich (Committee Member); Swarup Bhunia (Committee Member) Subjects: Computer Science