Random choices for churn resilient load balancing in peer-to-peer networks

Abstract

Peer-to-peer (P2P) networks based on consistent hashing functions have an inherent load uneven distribution problem. Things are even worse in unstructured P2P systems. The objective of load balancing in P2P networks is to balance the workload of the network nodes in proportion to their capacity so as to eliminate traffic bottleneck. It is challenging because of the dynamic nature of overlay networks and time-varying load characteristics. Random choices schemes can balance load effectively while incurring only a small overhead, making such schemes appealing for practical systems. Existing theoretical work analyzing properties of random choices algorithms can not be applied in the highly dynamic and heterogeneous P2P systems. In this paper, we characterize the behaviors of randomized search schemes in the general P2P environment. We extend the supermarket model by investigating the impact of node heterogeneity and churn to the load distribution in P2P networks. We prove that by using d-way random choices schemes, the length of the longest queue in P2P systems with heterogeneous nodal capacity and node churn for d ≥ 2 is clog logn/logd + O(1) with high probability, where c is a constant.