An overview of methods for handling evolving graph sequences

Abstract

Graph data structures constitute a prominent way to model real-world networks. Most of the graphs originating from these networks are dynamic and constantly evolving. The state (snapshot) of a graph at various time instances forms an evolving graph sequence. By incorporating temporal information in the traditional graph queries, valuable characteristics regarding the nature of a graph can be extracted such as the evolution of the shortest path distance between two vertices through time. Most modern graph processing systems are not suitable for this task since they operate on single very large graphs. In this work we review centralized and distributed methods and solutions proposed towards handling evolving graph sequences.