Title
Leveraging Computation Sharing And Parallel Processing In Location-Dependent Query Processing
Keywords
Continuous query; GPU; Graphical processing unit; Location-based services; Location-dependent query processing; Mobile database systems
Abstract
A variety of research exists for the processing of continuous queries in large, mobile environments. Each method tries, in its own way, to address the computational bottleneck of constantly processing so many queries. In this paper, we introduce an efficient and scalable system for monitoring continuous queries by leveraging the parallel processing capability of the Graphics Processing Unit. We examine a naive CPU-based solution for continuous range-monitoring queries, and we then extend this system using the GPU. Additionally, with mobile communication devices becoming commodity, location-based services will become ubiquitous. To cope with the very high intensity of location-based queries, we propose a view oriented approach of the location database, thereby reducing computation costs by exploiting computation sharing amongst queries requiring the same view. Our studies show that by exploiting the parallel processing power of the GPU, we are able to significantly scale the number of mobile objects, while maintaining an acceptable level of performance. © 2011 Springer Science+Business Media, LLC.
Publication Date
7-1-2012
Publication Title
Journal of Supercomputing
Volume
61
Issue
1
Number of Pages
215-234
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1007/s11227-011-0651-z
Copyright Status
Unknown
Socpus ID
84861983265 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84861983265
STARS Citation
Cazalas, Jonathan and Guha, Ratan, "Leveraging Computation Sharing And Parallel Processing In Location-Dependent Query Processing" (2012). Scopus Export 2010-2014. 4271.
https://stars.library.ucf.edu/scopus2010/4271