Divide and Conquer: Partitioning Online Social Networks

TL;DR

This paper analyzes the properties of large online social networks to guide effective partitioning strategies, aiming to improve system performance by leveraging network characteristics.

Contribution

It provides a comprehensive characterization of social network properties and evaluates various partitioning methods to inform better algorithm choices.

Findings

Different social network properties influence partitioning effectiveness

Trade-offs exist between partitioning methods based on network characteristics

Proper partitioning can significantly enhance OSN system performance

Abstract

Online Social Networks (OSNs) have exploded in terms of scale and scope over the last few years. The unprecedented growth of these networks present challenges in terms of system design and maintenance. One way to cope with this is by partitioning such large networks and assigning these partitions to different machines. However, social networks possess unique properties that make the partitioning problem non-trivial. The main contribution of this paper is to understand different properties of social networks and how these properties can guide the choice of a partitioning algorithm. Using large scale measurements representing real OSNs, we first characterize different properties of social networks, and then we evaluate qualitatively different partitioning methods that cover the design space. We expose different trade-offs involved and understand them in light of properties of social networks. We show that a judicious choice of a partitioning scheme can help improve performance.