TrajStore: An Adaptive Storage System for Very Large Trajectory Data Sets
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Madden_Trajstore an.pdf
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1 MB
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Author(s)
Cudre-Mauroux, Philippe
Wu, Eugene
Madden, Samuel R.
Date Issued
April 2010
Journal
IEEE 26th International Conference on Data Engineering (ICDE), 2010
Publisher
Institute of Electrical and Electronics Engineers
Citation
Cudre-Mauroux, P., E. Wu, and S. Madden. “TrajStore: An Adaptive Storage System for Very Large Trajectory Data Sets.” Data Engineering (ICDE), 2010 IEEE 26th International Conference On. 2010. 109-120.
Version
Author's final manuscript
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution-Noncommercial-Share Alike 3.0
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DOI of Published Version
https://doi.org/10.1109/ICDE.2010.5447829
