Maintaining Data Consistency in Structured P2P Systems

Abstract

A fundamental challenge of supporting mutable data replication in a Peer-to-Peer (P2P) system is to efficiently maintain consistency. This paper presents a framework for Balanced Consistency Maintenance (BCoM) in structured P2P systems with heterogeneous node capabilities and various workload patterns. Replica nodes of each object are organized into a tree structure for disseminating updates, and a sliding window update protocol is developed for consistency maintenance. We present an analytical model to optimize the window size according to the dynamic network conditions, workload patterns and resource limits. In this way, BCoM balances the consistency strictness, object availability for updates, and update propagation performance for various application requirements. On top of the dissemination tree, two enhancements are proposed: (1) a fast recovery scheme to strengthen the robustness against node and link failures, and (2) a node migration policy to remove and prevent bottlenecks allowing more efficient update delivery. Simulations are conducted using P2PSim to evaluate BCoM in comparison to SCOPE [1]. The experimental results demonstrate that BCoM outperforms SCOPE with lower discard rates. BCoM achieves a discard rate as low as 5 percent in most cases while SCOPE has almost 100 percent discard rate.