Uncertain voronoi cell computation based on space decomposition

LNCS v. 9239 entitled: Advances in Spatial and Temporal Databases: 14th International Symposium, SSTD 2015 ... ProceedingsThe problem of computing Voronoi cells for spatial objects whose locations are not certain has been recently studied. In this work, we propose a new approach to compute Voronoi cells for the case of objects having rectangular uncertainty regions. Since exact computation of Voronoi cells is hard, we propose an approximate solution. The main idea of this solution is to apply hierarchical access methods for both data and object space. Our space index is used to efficiently find spatial regions which must (not) be inside a Voronoi cell. Our object index is used to efficiently identify Delauny relations, i.e., data objects which affect the shape of a Voronoi cell. We develop three algorithms to explore index structures and show that the approach that descends both index structures in parallel yields fast query processing times. Our experiments show that we are able to approximate uncertain Voronoi cells much more effectively than the state-of-the-art, and at the same time, improve run-time performance.postprin

Probabilistic Granule-Based Inside and Nearest Neighbor Queries

Abstract. The development of location-based services and advances in the field of mobile computing have motivated an intensive research effort devoted to the efficient processing of location-dependent queries. In this context, it is usually assumed that location data are expressed at a fine geographic precision. Adding support for location granules means that the user is able to use his/her own terminology for locations (e.g., GPS, cities, states, provinces, etc.), which may have an impact in the semantics of the query, the way the results are presented, and the performance of the query processing. Along with its advantages, the management of the so-called location granules introduces new challenges for query processing. In this paper, we analyze two popular location-dependent constraints, inside and nearest neighbors, and enhance them with the possibility to specify location granules. In this context, we study the problem that arises when the locations of the objects are subject to some imprecision.