Snapshot location-based query processing on moving objects in road networks

Abstract

Location-based services are increasingly popular and it is a key challenge to efficiently support query processing. We present a novel design to process large numbers of location-based snapshot queries on MOVing objects in road Networks (MOVNet, for short). MOVNet's dual-index design utilizes an on-disk R-tree to store the network connectivities and an in-memory grid structure to maintain moving object position updates. A method to speedily compute the overlapping grid cells in the network relates these two indices. Based on the above features we propose algorithms to support mobile network distance range queries. We demonstrate via experimental results that MOVNet yields excellent performance while scaling to a very large number of moving objects.