Regular Polygon Based Search Algorithm for Processing Maximum Range Queries

Abstract

Location Based Services (LBS) for supporting a group of mobile users are potentially promising. This article considers one of these LBS, which provides a group of mobile users, each at a different location, with location-dependent information in their neighborhood. Location-dependent queries, such as Aggregate k- Nearest Neighbor (k-ANN) queries and Aggregate Range queries, are indispensable to the LBS. However, supporting location-dependent queries suffers from two difficulties. One is concerned with access to several databases operating autonomously at remote sites. The other is concerned with simple and restrictive Web API interfaces to access the databases. A revised version of Regular Polygon based Search Algorithm (RPSA) is applied to overcome the difficulties, which requests a series of k-Nearest Neighbor (k-NN) queries to process approximate Aggregate Range queries on a single remote spatial database. RPSA is experimentally evaluated by applying it to Maximum Range queries which are a type of Aggregate Range queries. The results show that Precision is over 0.87 for uniformly distributed dataset and over 0.92 for skew-distributed dataset. Also, Number of Requests (NOR) ranges from 3.2 to 4.3, and from 3.9 to 4.9, respectively. Besides, the case study regarding the real dataset of public facilities shows that Precision is over 0.9 on the average, except in case of Maximum 10-th Range queries. On the other hand, NOR ranges from 3.5 to 4.3 on the average.