The concept of resource pool has a very long history. Propelled by the need to share CPU cycles of supercomputers for high-throughput computing jobs from the scientific community, the vision is most recently explored by the advocates of Grid. On the other hand, the advent of P2P researches has demonstrated the feasibility of integrating potentially unlimited amount of less powerful machines around the world. Organizing a P2P resource pool thus becomes an interesting research topic.

This paper attempts to address two problems. The first is how to organize a P2P resource pool, and our answer is to combine the self-organizing strength of P2P DHT with an in-system, self-scaling monitoring infrastructure that is layered on top of DHT. The second question is the utility of the P2P resource pool for interesting applications. And we choose to showcase its power by optimizing wide-area application level multicasting (ALM), a problem far more challenging and interesting than conventional tasks such as massively parallel computation.

We show that utilizing spare resources in the pool results in significant savings for single ALM session. Furthermore, we adopt a purely market-driven approach to optimize multiple concurrent sessions. As expected, sessions of higher priority are given higher share of resources.