D-Grid: An In-Memory Dual Space Grid Index for Moving Object Databases

The rapid development of positioning techniques has enabled information to be widely collected on continuously moving objects, such as vehicles and mobile device users. Database systems supporting massive updates and predictive spatio-temporal queries on the moving objects are essential for modern location-based services. On the other hand, information (e.g. Location and velocity) that describes the motion of millions of moving objects can be accommodated in main memory with modern computing machines. Thus, in-memory indexing techniques are gaining popularity among moving object databases. Recent works indicate that a simple uniform grid is one of the best choices for indexing moving objects in main memory. However, to the best of our knowledge, relevant works in the literature consider only grids in the location space but disregard the velocity information of the moving objects, which we believe can be exploited to further improve query performance. In this paper, we propose D-Grid, an in-memory dual space grid index for moving objects. Specifically, it indexes moving objects using grid structures in both location and velocity spaces, which improves query performance by almost an order of magnitude. We also propose a lazy deletion and garbage cleaning mechanism that can be applied to both our dual space and existing location space uniform grid based indexes and further improve update performance. Extensive experiments demonstrate that our approach significantly outperforms existing uniform grid based in-memory indexes.