SIEF: Efficiently Answering Distance Queries for Failure Prone Graphs

Abstract

Shortest path computation is one of the most fundamental operations for managing and analyzing graphs. A number of methods have been proposed to answer shortest path distance queries on static graphs. Unfortunately, there is little work on answering distance queries on dynamic graphs, particularly graphs with edge failures. Today’s real-world graphs, such as the social network graphs and web graphs, are evolving all the time and link failures occur due to various factors, such as people stopping following others on Twitter or web links becoming invalid. Therefore, it is of great importance to handle distance queries on these failureprone graphs. This is not only a problem far more difficult than that of static graphs but also important for processing distance queries on evolving or unstable networks. In this paper, we focus on the problem of computing the shortest path distance on graphs subject to edge failures. We propose SIEF, a Supplemental Index for Edge Failures on a graph, which is based on distance labeling. Together with the original index created for the original graph, SIEF can support distance queries with edge failures efficiently. By exploiting properties of distance labeling on static graphs, we are able to compute very compact distance labeling for all singe-edge failure cases on dynamic graphs. We extensively evaluate our algorithms using six real-world graphs and confirm the effectiveness and efficiency of our approach.