Title

Geds: Gpu Execution Of Continuous Queries On Spatio-Temporal Data Streams

Keywords

Computation sharing; Continuous query; GPU; Graphical processing unit; Location-based services; Mobile database systems; Parallel processing; Spatio-temporal data streams

Abstract

Much research exists for the efficient processing of spatio-temporal data streams. However, all methods ultimately rely on an ill-equipped processor [22], 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. © 2010 IEEE.

Publication Date

12-1-2010

Publication Title

Proceedings - IEEE/IFIP International Conference on Embedded and Ubiquitous Computing, EUC 2010

Number of Pages

112-119

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/EUC.2010.26

Socpus ID

79951784004 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/79951784004

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