Dynamic histograms for future spatiotemporal range predicates

In this paper we present a new method to efficiently process the approximate answers for future location-based query predicates on demand by using spatiotemporal histograms. Based on the concepts of entropy and marginal distribution, we build spatiotemporal histograms for the movement parameters, which result in the avoidance of reconstructing histograms. Using spatiotemporal histograms, the approximate future query processing can be achieved efficiently. In addition, we clarify and evaluate our proposed method with several experiments.