| Querying the trajectories of on-line mobile objects |
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International Workshop on Data Engineering for Wireless and Mobile Access
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Proceedings of the 2nd ACM international workshop on Data engineering for wireless and mobile access
table of contents
Santa Barbara, California, United States
Pages: 66 - 73
Year of Publication: 2001
ISBN:1-58113-412-6
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Authors
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Dieter Pfoser
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Department of Computer Science, Aalborg University, Fredrik. Bajers Vej 7E, DK-9220 Aalborg øst, Denmark
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Christian S. Jensen
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Department of Computer Science, Aalborg University, Fredrik. Bajers Vej 7E, DK-9220 Aalborg øst, Denmark
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Downloads (6 Weeks): 5, Downloads (12 Months): 26, Citation Count: 7
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ABSTRACT
Position data is expected to play a central role in a wide range of mobile computing applications, including advertising, leisure, safety, security, tourist, and traffic applications. Applications such as these are characterized by large quantities of wirelessly Internet-worked, position-aware mobile objects that receive services where the objects' position is essential. The movement of an object is captured via sampling, resulting in a trajectory consisting of a sequence of connected line segments for each moving object. This paper presents a technique for querying these trajectories. The technique uses indices for the processing of spatiotemporal range queries on trajectories. If object movement is constrained by the presence of infrastructure, e.g., lakes, park areas, etc., the technique is capable of exploiting this to reduce the range query, the purpose being to obtain better query performance. Specifically, an algorithm is proposed that segments the original range query based on the infrastructure contained in its range. The applicability and limitations of the proposal are assessed via empirical performance studies with varying datasets and parameter settings.
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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Moore, D.: Fast Hilbert Curve Generation, Sorting, and Range Queries. www.caam.rice.edu/~dougm/twiddle/Hilbert/, current as of April 12, 2001.
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Pfoser, D. and Jensen, C. S.: Querying the Trajectories of On- Line Mobile Objects. TimeCenter Technical Report TR-55, www.cs.auc.dk/TimeCenter, current as of April 12, 2001.
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Pfoser, D. and Theodoridis, Y.: Generating Semantics-Based Trajectories of Moving Objects. In Proceedings of the International Workshop on Emerging Technologies for Geo-Based Applications, pp. 59-76, 2000.
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CITED BY 7
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Arnon Amir , Alon Efrat , Jussi Myllymaki , Lingeshwaran Palaniappan , Kevin Wampler, Buddy tracking - efficient proximity detection among mobile friends, Pervasive and Mobile Computing, v.3 n.5, p.489-511, October, 2007
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