A neighbor peer organization and behavior prediction scheme of P2P streaming systems(POPP)is proposed to solve the lack of analysis on single node's long-term behavior in current study of streaming system user behavior. The POPP bases on the inter and self behavior correlations of nodes
and collects information of neighbor peers such as behavior
delay and bandwidth in data cooperation process
to calculate their comprehensive availability and to maintain a list of the candidate peers that may provide high quality service. Then
future online status of neighbor peers is predicted by a Markov chain model. Simulations driven by a trace of streaming system show that the neighbor organization of POPP effectively improves the service quality of neighbors
and that the neighbor status prediction accuracy reaches more than 97% after enough trainings.
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