Novel Approaches to the Indexing of Moving Object Trajectories

The domain of spatiotemporal applications is a treasure trove of new types of data and queries. However, work in this area is guided by related research from the spatial and temporal domains, so far, with little attention towards the true nature of spatiotemporal phenomena. In this work, the focus is on a spatiotemporal sub-domain, namely the trajectories of moving point objects. We present new types of spatiotemporal queries, as well as algorithms to process those. Further, we introduce two access methods this kind of data, namely the Spatio-Temporal R-tree (STR-tree) and the Trajectory-Bundle tree (TB-tree). The former is an R-tree based access method that considers the trajectory identity in the index as well, while the latter is a hybrid structure, which preserves trajectories as well as allows for R-tree typical range search in the data. We present performance studies that compare the two indices with the R-tree (appropriately modified, for a fair comparison) under a varying set of spatiotemporal queries, and we provide guidelines for a successful choice among them.