The streaming capacity of sparsely-connected P2P systems with distributed control

Peer-to-Peer (P2P) streaming technologies can take advantage of the upload capacity of clients, and hence can scale to large content distribution networks with lower cost. A fundamental question for P2P streaming systems is the maximum streaming rate that all users can sustain. Prior works have studied the optimal streaming rate for a complete network, where every peer is assumed to communicate with all other peers. This is however an impractical assumption in real systems. In this paper, we are interested in the achievable streaming rate when each peer can only connect to a small number of neighbors. We show that even with a random peer selection algorithm and uniform rate allocation, as long as each peer maintains Ω(log N) downstream neighbors, where N is the total number of peers in the system, the system can asymptotically achieve a streaming rate that is close to the optimal streaming rate of a complete network.We then extend our analysis to multi-channel P2P networks, and we study the scenario where “helpers” from channels with excessive upload capacity can help peers in channels with insufficient upload capacity. We show that by letting each peer select Ω(log N) neighbors randomly from either the peers in the same channel or from the helpers, we can achieve a close-to-optimal streaming capacity region. Simulation results are provided to verify our analysis.