G*-Tree: An Efficient Spatial Index on Road Networks

In this paper, we propose an efficient hierarchical index, G*-tree, to optimize spatial queries on road networks. Most existing graph indexes can only support one kind of query, and thus we need to build multiple indexes on a road network to handle various kinds of spatial queries, which is inefficient and unscalable for real-world applications. To address the problem, a recent study proposes G-tree to support multiple types of spatial queries on road networks within one framework. However, the assembly-based method on G-tree is not efficient enough to handle spatial queries when vertices, which are close in a road network, are distant in G-tree. To address the inefficiency problem of G-tree, in this paper, we propose a novel index structure on road networks, namely G*-tree, whose key idea is to build shortcuts between selected leaf nodes. Based on G*-tree, we propose three shortcut-based algorithms to answer distance queries, k-nearest neighbor queries and range queries, respectively, which are more efficient than the existing assembly-based algorithms on G-tree. Moreover, we propose a shortcut selection algorithm to optimize the performance of spatial queries on G*-tree. We conduct extensive experiments to compare our G*-tree and the state-of-the-art indexing methods on various large-scale road networks, where the results demonstrate that our G*-tree has better efficiency and scalability than the competitors to handle spatial queries.