Adaptive content management in structured P2P communities

A fundamental paradigm in P2P is that of a large community of intermittently-connected nodes that cooperate to share files. Because nodes are intermittently connected, the P2P community must replicate and replace files as a function of their popularity to achieve satisfactory performance. We develop a suite of distributed, adaptive algorithms for replicating and replacing content in a P2P community. We do this for structured P2P communities, in which a distributed hash table (DHT) overlay is available for locating the node responsible for a key. In particular, we develop the Top-K MFR replication and replacement algorithm, which can be layered on top of a DHT overlay, and in addition adaptively converges to a nearly-optimal replication profile. Furthermore, we evaluate the file transfer load caused by the adaptive algorithms on each peer, and present two approaches for achieving a better load balance. Our evaluation shows that with our two algorithms, an arbitrary load distribution is possible, hence allowing each peer to serve requests at the rate it wishes.