Efficient Load Balancing In Peer-to-Peer Systems with Partial knowledge of the System

Load balancing is a critical issue for the efficient operation of peer-to- peer networks. With the notion of virtual servers, peers participating in a heterogeneous, structured peer-to-peer (P2P) network may host different numbers of virtual servers, and by migrating virtual servers, peers can balance their loads proportional to their capacities. Peers participating in a Distributed Hash Table (DHT) are often heterogeneous. The existing and decentralized load balance algorithms designed for the heterogeneous, structured P2P networks either explicitly construct auxiliary networks to manipulate global information or implicitly demand the P2P substrates organized in a hierarchical fashion. Without relying on any auxiliary networks and independent of the geometry of the P2P substrates, this paper present a novel efficient, proximity-aware load balancing algorithm by using the concept of virtual servers, that is unique in that each participating peer is based on the partial knowledge of the system to estimate the probability distributions of the capacities of peers and the loads of virtual servers