Using Dijkstra's algorithm to incrementally find the k-Nearest Neighbors in spatial network databases

Abstract

One of the most important kinds of queries in Spatial Network Databases (SNDB) to support Location-Based Services (LBS) is the k-Nearest Neighbors (k-NN) query. Given a point in a network, e.g. a location of a car on a road network, and a set of points of interests, e.g. hotels, gas stations, etc., the k-NN query returns the k points of interest closest to the query point. The network distance is used in such a query instead of the Euclidean distance. Dijkstra's algorithm is a well known solution to this problem. In this paper, we propose a storage schema with a set of index structures to support an efficient execution of a slightly modified version of the Dijkstra's algorithm. We show in an experimental evaluation with generated data sets that our proposal is more efficient than the state-of-the-art solution to this problem.