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ABSTRACT
The emergence of location-aware services calls for new real time spatio-temporal query processing algorithms that deal with large numbers of mobile objects and queries. Online query response is an important characterization of location-aware services. A delay in the answer to a query gives invalid and obsolete results, simply because moving objects can change their locations before the query responds. To handle large numbers of spatio-temporal queries efficiently, we propose the idea of sharing as a means to achieve scalability. In this paper, we introduce several types of sharing in the context of continuous spatio-temporal queries. Examples of sharing in the context of real-time spatio-temporal database systems include sharing the execution, sharing the underlying space, sharing the sliding time windows, and sharing the objects of interest. We demonstrate how sharing can be integrated into query predicates, e.g., selection and spatial join processing. The goal of this paper is to outline research directions and approaches that will lead to scalable and efficient location-aware services.
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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CITED BY 6
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Mohamed F. Mokbel , Xiaopeng Xiong , Walid G. Aref , Susanne E. Hambrusch , Sunil Prabhakar , Moustafa A. Hammad, PLACE: a query processor for handling real-time spatio-temporal data streams, Proceedings of the Thirtieth international conference on Very large data bases, p.1377-1380, August 31-September 03, 2004, Toronto, Canada
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