Processing Approximate Rank Queries in a Wireless Mobile Sensor Environment

Querying in the context of moving objects environments has been largely studied. Extensive research effort has also been dedicated to exploring different techniques of handling uncertainty, an issue intrinsic to the nature of node mobility. Current trends in moving object database-related applications impose the need to consider uncertainty from different perspectives. In this paper, we examine the case in which the exact locations of moving objects are never reported to the central database server. Instead, deductions about the objects positions are based on data gathered from the readings of mobile sensors. With this arrangement in mind, we introduce and study approximate rank queries, where a mobile object is in the answer set of a query with probability p and is assigned a rank with probability P. The rank reflects the objects approximate distance from the query point. Queries are evaluated based on different pruning techniques and ranking heuristics. Our work is backed with an extensive simulation study, which examines the effectiveness of the algorithm with varied numbers of mobile sensors and objects.