ReHub

Abstract

Quite recently, the algorithmic community has focused on solving multiple shortest-path query problems beyond simple vertex-to-vertex queries, especially in the context of road networks. Unfortunately, those advanced query-processing techniques cannot be applied to large-scale graphs, such as social or collaboration networks, or to efficiently answer reverse k -nearest neighbor (R k NN) queries, which are of practical relevance to a wide range of applications. To remedy this, we propose ReHub, a novel main-memory algorithm that extends the hub labeling technique to efficiently answer R k NN queries on large-scale networks. Our experimentation will show that ReHub is the best overall solution for this type of queries, requiring only minimal additional preprocessing and providing very fast query times in all cases.