Utility Maximization in Peer-to-Peer Systems

Joint work with Miroslav Ponec from Polytechnic University, and Sudipta Sengupta, Jin Li, and Philip A. Chou from Microsoft Research Redmond.

Peer-to-Peer (P2P) applications have witnessed unprecedented growth on the Internet and are increasingly being used for real-time applications like video conferencing and live streaming. However, the design of the majority of P2P systems does not strive to achieve any systematic optimization of the total value to all peers under a resource sharing constraint. This may well be the next step in improving the performance of P2P systems.

In this project, we study the problem of utility maximization over P2P topology, in which aggregate application-specific utilities are maximized by running distributed algorithms on P2P nodes that are constrained by their uplink capacities. This may be understood as extending Kelly’s seminal framework from single-path unicast over general topology to multi-path multicast over P2P topology, with network coding allowed.

For single-rate multicast over certain classes of popular P2P topologies, we show that routing along a linear number of trees per source can achieve the largest rate region that can be possibly obtained by (inter-session) network coding. Similarly, for multi-rate multicast, routing along a quadratic number of trees per source is sufficient to achieve the largest rate region attained by (intra-session) network coding.

This simplification result allows us to develop a new multi-tree routing formulation for the problem. This new tree-rate based formulation is unique in the sense that it not only eliminates some mathematical difficulties associated with link-rate or path-rate based formulations, but also leads to easy implementation. Despite of the negative results in literature on applying Primal-dual algorithms to maximize utility under multi-path settings, we have been able to develop a Primal-dual distributed algorithm to maximize the aggregate utility under the multi-path routing environments. We first characterize the convergence behavior of the Primal-dual algorithm under multi-path settings, and then utilize our proposed sufficient condition to show its global exponential convergence to the optimal solution under different P2P communication scenarios we study. The primal-dual algorithm can be implemented by utilizing only end-to-end delay measurements between P2P nodes; hence, it can be readily deployed on today’s Internet. To support this claim, we have implemented the Primal-dual algorithm for use in a peer-assisted multi-party conferencing system and evaluated its performance through actual experiments on a LAN testbed and the Internet.


  • M. Chen, M. Ponec, S. Sengupta, J. Li, and P. A. Chou, “Utility Maximization in Peer-to-Peer Systems”, accepted for publication in IEEE/ACM Trans. on Networking. [ final version to be available ] (A conference version appears in ACM SIGMETRICS 2008 [PDF])

  • M. Ponec, S. Sengupta, M. Chen, J. Li, and P. A. Chou, “Optimizing Multi-rate Peer-to-Peer Video Conferencing Applications”, IEEE Trans. on Multimedia, special issue on Iterative Multimedia, Oct. 2011. [PDF] (A conference version appears in IEEE ICME 2009 as a plenary paper and receives the Best Paper Award. [PDF])

  • S. Sengupta, M. Chen, P. A. Chou, and J. Li, “On Optimality of Routing for Multi-source Multicast Communication Scenarios with Node Uplink Constraints”, Proceeding of 2008 IEEE International Symposium on Information Theory (ISIT 2008), Toronto, Ontario, Canada, July 6-11, 2008. [PDF]