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Parallel In-Memory Distance Threshold Queries on Trajectory Databases

Authors:
Michael Gowanlock
Henri Casanova
David Schanzenbach

Keywords: spatiotemporal databases; query parallelization.

Abstract:
Spatiotemporal databases are utilized in many applications to store the trajectories of moving objects. In this context, we focus on in-memory distance threshold queries that return all trajectories found within a distance d of a fixed or moving object over a time interval. We present performance results for a sequential query processing algorithm that uses an in-memory R-tree index, and we find that decreasing index resolution improves query response time. We then develop a simple multithreaded implementation and find that high parallel efficiency (78%-90%) can be achieved in a shared memory environment for a set of queries on a real-world dataset. Finally, we show that a GPGPU approach can achieve a speedup over 3.3 when compared to the multithreaded implementation. This speedup is obtained by abandoning the use of an index-tree altogether. This is an interesting result since index-trees have been the cornerstone of efficiently processing spatiotemporal queries.

Pages: 80 to 83

Copyright: Copyright (c) IARIA, 2014

Publication date: April 20, 2014

Published in: conference

ISSN: 2308-4332

ISBN: 978-1-61208-334-6

Location: Chamonix, France

Dates: from April 20, 2014 to April 24, 2014