2013 IEEE 29th International Conference on Data Engineering (ICDE) (2010)
Long Beach, CA, USA
Mar. 1, 2010 to Mar. 6, 2010
Samuel Madden , MIT CSAIL, USA
Eugene Wu , MIT CSAIL, USA
Philippe Cudre-Mauroux , MIT CSAIL, USA
The rise of GPS and broadband-speed wireless devices has led to tremendous excitement about a range of applications broadly characterized as “location based services”. Current database storage systems, however, are inadequate for manipulating the very large and dynamic spatio-temporal data sets required to support such services. Proposals in the literature either present new indices without discussing how to cluster data, potentially resulting in many disk seeks for lookups of densely packed objects, or use static quadtrees or other partitioning structures, which become rapidly suboptimal as the data or queries evolve. As a result of these performance limitations, we built TrajStore, a dynamic storage system optimized for efficiently retrieving all data in a particular spatiotemporal region. TrajStore maintains an optimal index on the data and dynamically co-locates and compresses spatially and temporally adjacent segments on disk. By letting the storage layer evolve with the index, the system adapts to incoming queries and data and is able to answer most queries via a very limited number of I/Os, even when the queries target regions containing hundreds or thousands of different trajectories.
Samuel Madden, Eugene Wu, Philippe Cudre-Mauroux, "TrajStore: An adaptive storage system for very large trajectory data sets", 2013 IEEE 29th International Conference on Data Engineering (ICDE), vol. 00, no. , pp. 109-120, 2010, doi:10.1109/ICDE.2010.5447829