Efficient and scalable query processing methods for finding the optimal spatial location

Abstract

In the era of mobile devices, location-based services are being used in a variety of contexts such as emergency, navigation, and entertainment, which demand scalable and efficient query processing on a large amount of spatial data. Most existing works in traditional spatial databases, however, have focused on finding some objects rather than finding some locations. This dissertation deals with various problems of finding the optimal location that satisfies a given set of conditions.

First, we study the maximizing range sum (MaxRS) problem and its variants in spatial databases. Given a set of weighted points and a rectangular region r of a given size, the goal of the MaxRS problem is to find a location of r such that the sum of the weights of all the points covered by r is maximized. This problem is useful in many location-based applications such as finding the best place for a new franchise store with a limited delivery range and finding the most attractive place for a tourist with a limited reachable range. In this dissertation, we propose a scalable external-memory algorithm (ExactMaxRS) for the MaxRS problem, which is optimal in terms of the I/O complexity. Furthermore, we propose an approximation algorithm (ApproxMaxCRS) for the MaxCRS problem that is a circle version of the MaxRS problem. Finally, we invent an output-sensitive external-memory algorithm (TwoPhaseMaxRS) for the AllMaxRS problem which extends MaxRS for all the optimal locations with the same best score to be retrieved. From a thorough theoretical study, we prove the correctness and optimality of ExactMaxRS, the approximation bound of ApproxMaxCRS, and the soundness and completeness of the result returned from TwoPhaseMaxRS.

With the same motivation as MaxRS, this dissertation also tackles the conventional kNN search problem, which allows the introduction of a new variant of the kNN query, called the nearest neighborhood (NNH) query. The NNH query aims to find the nearest location of the s...