Recent development of wireless technology and smart mobile devices has spurred intense research efforts to address spatial queries. In particular, an increasing interest for tackling spatial query processing in broadcast environments has been observed. To the best of our knowledge, most of the existing work on this problem has assumed an Euclidean space. However, for real applications, query clients move within a road sensor network, where the distance between a data object and a query is determined by the connectivity of the road sensor network. This paper explores the problem of spatial query processing in road sensor networks by means of wireless data broadcast. We present an efficient method to partition the record-keeping information about the underlying road sensor network and its associated objects, by which we develop a fully distributed air index, called integrated exponential index, based on an extended version of the Hilbert curve. We also propose efficient client-side algorithms to facilitate the processing of several kinds of spatial queries, including kNN query, CkNN query, and range query. Finally, extensive simulation experiments have been conducted to demonstrate the strengths of our proposed techniques.
All Science Journal Classification (ASJC) codes