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Scalable processing of trajectory-based queries in space-partitioned moving objects databases
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Geographic Information Systems archive
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems table of contents
Irvine, California
SESSION: Trajectories table of contents
Article No. 31  
Year of Publication: 2008
ISBN:978-1-60558-323-5
Authors
Ralph Lange  Institute of Parallel and Distributed Systems, Stuttgart, Germany
Frank Dürr  Institute of Parallel and Distributed Systems, Stuttgart, Germany
Kurt Rothermel  Institute of Parallel and Distributed Systems, Stuttgart, Germany
Sponsors
: Google
: Oak Ridge National Laboratory
: ESRI
Microsoft : Microsoft
Publisher
ACM  New York, NY, USA
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ABSTRACT

Space-partitioned Moving Objects Databases (SP-MODs) allow for the scalable, distributed management of large sets of mobile objects' trajectories by partitioning the trajectory data to a network of database servers.

Processing a spatio-temporal query q therefore requires efficiently routing q to the servers storing the affected trajectory segments. With a coordinate-based query --- like a spatio-temporal range query --- the relevant servers are directly determined by the queried range. However, with trajectory-based queries --- like retrieving the distance covered by a certain object during a given time interval --- the relevant servers depend on actual movement of the queried object. Therefore, efficient routing mechanisms for trajectory-based queries are an important challenge in SP-MODs.

In this paper, we present the Distributed Trajectory Index (DTI) that allows for such efficient query routing by creating an overlay network for each trajectory. We further present an enhanced index called DTI+S. It accelerates the processing of queries on aggregates of dynamic attributes, like the maximum speed during a time interval, by augmenting DTI with summaries of trajectory segments. Our simulations with a network of 1000 database servers show that DTI+S can reduce the overall processing time by more than 98%.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Ralph Lange: colleagues
Frank Dürr: colleagues
Kurt Rothermel: colleagues