An Efficient Evaluation of Spatial Search on Road Networks Using G-Tree

Abstract

Location-based services (LBS) enable users to question the purpose of interest like restaurants, hospitals with various features. Although optimal route calculation in road network supported distance may be a combinatorial optimization problem, with the advancement of varied web mapping services, it is possible to produce travel distance for LBS applications. Road network and site data easily are often represented as a graph during a spatial database. By using different spatial functions like pg-routing Dijikstra or pg-Routing A*, we will efficiently calculate the route from it. But in case of extremely large dataset, searching route and finding nearest neighbors are far more difficult. So here a completely unique indexing method for the road network is proposed. G-Tree indexing is an indexing method that efficiently supports mainly two queries,i.e., k-NN queries, single-pair shortest path query. G-Tree indexing method is inspired by R-Tree. Inspired by R-Tree, G-Tree may be a height-balanced and scalable index, namely G-Tree, to efficiently support these queries. The space complexity of G-Tree is O(│V│log│V│), where │V│ is the number of vertices within the road network. Finding only one shortest path to a point of interest (POI) is not sufficient for many situations like road conditions, traffic, etc. So this paper also suggests the method for calculating k alternating paths to a point of interest (POI) by using Yen’s algorithm and G-Tree.