SEARCH LOCATION-DEPENDENT DATA IN BROADCASTING ENVIRONMENT

Abstract

Location-based services (LBSs) provide the information based oil location information as specified in a query. Queries that support LBS are called Location-Dependent Queries (LDQ). LDQ contain: range query. nearest neighbor (NN) query, k-nearest neighbor (KNN) query and reverse nearest neighbor (RNN) query. Examples of mobile LBSs include location-dependent information access (e.g.. traffic reports and attractions) and nearest neighbor queries (e.g. finding the nearest restaurant). While LDQ is well studied in the traditional wired, disk-based client-server environment. it has not yet been tackled in relation to a wireless broadcasting environment. In this paper. the issues involved with organizing location-dependent data and answering LDQ queries on the air. are investigated. The linear properly of wireless broadcasting media and the power conservation requirement of mobile devices make the problem particularly interesting and challenging. An efficient data organization, called Jump R(Inn-Tree. and the corresponding search algorithm are proposed. The performance of the proposed Jump, is evaluated Rdnn-Tree and other traditional indexes (enhanced for wireless broadcasting) by using both uniform and skew data. The result shows that Jump Rdnn-Tree substantially outperforms the traditional indexes.