Fuzzy Distance-Based Range Queries over Uncertain Moving Objects

Data obtained from real world are imprecise or uncertain due to the accuracy of positioning devices, updating protocols or characteristics of applications. On the other hand, users sometimes prefer to qualitatively express their requests with vague conditions and different parts of search region are in-equally important in some applications. We address the problem of efficiently processing the fuzzy range queries for uncertain moving objects whose whereabouts in time are not known exactly, for which the basic syntax is find objects always/sometimes near to the query issuer with the qualifying guarantees no less than a given threshold during a given temporal interval. We model the location uncertainty of moving objects on the utilization of probability density functions and describe the indeterminate boundary of query range with fuzzy set. We present the qualifying guarantee evaluation of objects, and propose pruning techniques based on the α-cut of fuzzy set to shrink the search space efficiently. We also design rules to reject non-qualifying objects and validate qualifying objects in order to avoid unnecessary costly numeric integrations in the refinement step. An extensive empirical study has been conducted to demonstrate the efficiency and effectiveness of algorithms under various experimental settings.