Dynamic resource allocation for credit-based peer-to-peer multimedia streaming networks

Credit-based incentive mechanisms are widely adopted in today´s peer-to-peer (P2P) multimedia streaming systems due to their effectiveness in fighting against “free-riding” and stimulating the cooperation between peers. In this paper, we investigate the optimal and suboptimal credits allocation strategies for peers to maximize their viewing experience in such systems. Especially, the dynamic changing feature of credits is taken into consideration when we formulate the problem, and the optimal credits allocation is shown to be a staircase-like function over time. Then, based on the special features of the optimal credits allocation strategy, an effective double-loop iterative algorithm is proposed. For the consideration of practical implementation, three low-complexity suboptimal credits allocation strategies are proposed. It is shown that each of the suboptimal strategies has its own feature and is applicable to different scenarios.