Updating and Querying Databases that Track Mobile Units
Distributed and Parallel Databases - Special issue on mobile data management and applications
IEEE Transactions on Computers
Databases for Tracking Mobile Units in Real Time
ICDT '99 Proceedings of the 7th International Conference on Database Theory
Modeling Moving Objects for Location Based Services
IMWS '01 Revised Papers from the NSF Workshop on Developing an Infrastructure for Mobile and Wireless Systems
Location-based spatial queries
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Main Memory Evaluation of Monitoring Queries Over Moving Objects
Distributed and Parallel Databases
Fast computation of database operations using graphics processors
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
SINA: scalable incremental processing of continuous queries in spatio-temporal databases
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Managing uncertainty in moving objects databases
ACM Transactions on Database Systems (TODS)
Monitoring k-Nearest Neighbor Queries over Moving Objects
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Conceptual partitioning: an efficient method for continuous nearest neighbor monitoring
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
A Threshold-Based Algorithm for Continuous Monitoring of k Nearest Neighbors
IEEE Transactions on Knowledge and Data Engineering
Real-Time Processing of Range-Monitoring Queries in Heterogeneous Mobile Databases
IEEE Transactions on Mobile Computing
GPUTeraSort: high performance graphics co-processor sorting for large database management
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
MobiEyes: A Distributed Location Monitoring Service Using Moving Location Queries
IEEE Transactions on Mobile Computing
The TPR*-tree: an optimized spatio-temporal access method for predictive queries
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Continuous range monitoring of mobile objects in road networks
Data & Knowledge Engineering
Relational joins on graphics processors
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
On Reducing Communication Cost for Distributed Moving Query Monitoring Systems
MDM '08 Proceedings of the The Ninth International Conference on Mobile Data Management
Distributed Real-Time Processing of Range-Monitoring Queries in Heterogeneous Mobile Databases
ICCIT '08 Proceedings of the 2008 Third International Conference on Convergence and Hybrid Information Technology - Volume 01
Smart phone for mobile commerce
Computer Standards & Interfaces
A Fast Similarity Join Algorithm Using Graphics Processing Units
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Leveraging Computation Sharing and Parallel Processing in Location-Based Services
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 02
Efficient Evaluation of k-Range Nearest Neighbor Queries in Road Networks
MDM '10 Proceedings of the 2010 Eleventh International Conference on Mobile Data Management
Distributed continuous range query processing on moving objects
DEXA'06 Proceedings of the 17th international conference on Database and Expert Systems Applications
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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.