Title
Leveraging Computation Sharing And Parallel Processing In Location-Based Services
Keywords
Continuous query; GPU; Graphical processing unit; Location-based services; 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 rangemonitoring 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 locationbased 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. © 2009 IEEE.
Publication Date
12-3-2009
Publication Title
Proceedings - 12th IEEE International Conference on Computational Science and Engineering, CSE 2009
Volume
2
Number of Pages
221-228
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/CSE.2009.437
Copyright Status
Unknown
Socpus ID
70749126912 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/70749126912
STARS Citation
Cazalas, Jonathan and Hua, Kien, "Leveraging Computation Sharing And Parallel Processing In Location-Based Services" (2009). Scopus Export 2000s. 11291.
https://stars.library.ucf.edu/scopus2000/11291