Optimizing Inter-server Communication for Online Social Networks

Abstract

Distributed storage systems are the key infrastructures for hosting the user data of large-scale Online Social Networks (OSNs). The amount of inter-server communication is an important scalability indicator for these systems. Data partitioning and replication are two inter-related issues affecting the inter-server traffic caused by user-initiated read and write operations. This paper investigates the problem of minimizing the total inter-server traffic among a cluster of OSN servers through joint partitioning and replication optimization. We propose a Traffic-Optimized Partitioning and Replication (TOPR) method based on an analysis of how replica allocation affects the interserver communication. Lightweight algorithms are developed to adjust partitioning and replication dynamically according to data read and write rates. Evaluations with real Facebook and Twitter social graphs show that TOPR significantly reduces the interserver communication compared with state-of-the-art methods.