Embedded and Ubiquitous Computing, IEEE/IFIP International Conference on (2010)
Hong Kong, China
Dec. 11, 2010 to Dec. 13, 2010
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/EUC.2010.26
Much research exists for the efficient processing of spatio-temporal data streams. However, all methods ultimately rely on an ill-equipped processor , namely a CPU, to evaluate concurrent, continuous spatio-temporal queries over these data streams. This paper presents GEDS, a scalable, Graphics Processing Unit (GPU)-based framework for the evaluation of continuous spatio-temporal queries over spatio-temporal data streams. GEDS employs the computation sharing and parallel processing paradigms to deliver scalability in the evaluation of continuous spatio-temporal queries. The GEDS framework utilizes the parallel processing capability of the GPU, a stream processor by trade, to handle the computation required in this application. Experimental evaluation shows promising performance and shows the scalability and efficacy of GEDS in spatio-temporal data streaming environments.
spatio-temporal data streams, computation sharing, parallel processing, location-based services, mobile database systems, continuous query, graphical processing unit, GPU
Jonathan Cazalas, Ratan Guha, "GEDS: GPU Execution of Continuous Queries on Spatio-Temporal Data Streams", Embedded and Ubiquitous Computing, IEEE/IFIP International Conference on, vol. 00, no. , pp. 112-119, 2010, doi:10.1109/EUC.2010.26