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.
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References
Bao J, Chow C-Y, Mokbel MF, Ku W-S (2010) Efficient evaluation of k-range nearest neighbor queries in road networks. In: Proceedings of the international conference on mobile data management, MDM 2010, Kansas City, MO, May
Cai Y, Hua KA (2002) Managing continuous range queries in mobile databases. In: Mobile and wireless communications network, 2002. 4th international workshop, pp 441–445
Cai Y, Hua KA, Cao G, Xu T (2006) Real-time processing of range-monitoring queries in heterogeneous mobile databases. IEEE Trans Mob Comput 5(7):931–942
Cazalas J, Hua K (2009) Leveraging computation sharing and parallel processing in location-based services. In: Proceedings of the 2009 international conference on computational science and engineering, pp 221–228
Chang YF, Chen CS, Zhou H (2009) Smart phone for mobile commerce. Comput Stand Interfaces 31(4):740–747
Gedik B, Liu L (2006) MobiEyes: a distributed location monitoring service using moving location queries. IEEE Trans Mob Comput 5(10):1384–1402
Govindaraju N, Lloyd B, Wang W, Lin M, Manocha D (2004) Fast computation of database operations using graphics processors. In: SIGMOD
Govindaraju N, Gray J, Kumar R, Manocha D (2006) GPUTeraSort: high performance graphics coprocessor sorting for large database management. In: SIGMOD
He B, Yang K, Fang R, Lu M, Govindaraju N, Luo Q, Sander P (2008) Relational joins on graphics processors. In: Proceedings of the 2008 ACM SIGMOD international conference on management of data
Kalashnikov DV, Prabhakar S, Hambrusch SE (2004) Main memory evaluation of monitoring queries over moving objects. Distrib Parallel Databases (Mar):117–135
Lieberman MD, Sankaranarayanan J, Samet H (2008) A fast similarity join algorithm using graphics processing units. In: ICDE
Liu F, Hua KA, Fei X (2008) On reducing communication cost for distributed moving query monitoring systems. In: Mobile data management, 2008. MDM ’08, 9th international conference on, 27–30 April, pp 156–164
Mokbel MF, Xiong X, Aref WG (2004) SINA: scalable incremental processing of continuous queries in spatio-temporal databases. In: Proc ACM SIGMOD int’l conf management of data
Mouratidis K, Hadjieleftheriou M, Papadias D (2005) Conceptual partitioning: an efficient method for continuous nearest neighbor monitoring. In: SIGMOD
Mouratidis K, Papadias D, Bakiras S, Tao Y (2005) A threshold-based algorithm for continuous monitoring of k nearest neighbors. IEEE Trans Knowl Data Eng 17(11):1451–1464
Prabhakar S, Xia Y, Kalashnikov D, Aref WG, Hambrusch S (2000) Queries as data and expanding indexes: techniques for continuous queries on moving objects. In: TR., Dept. of computer science, Purdue Univ
Prabhakar S, Xia Y, Kalashnikov D, Aref WG, Hambrusch S (2002) Query indexing and velocity constrained indexing: scalable techniques for continuous queries on moving objects. IEEE Trans Comput 15(10):1124–1140
Predic B, Stojanovic D (2005) A framework for handling mobile objects in location based services. In: Proceedings AGILE conference, pp 419–427
Stojanovic D, Papadopoulos AN, Predic B, Djordjevic-Kajan S, Nanopoulos A (2007) Continuous range query monitoring of mobile objects in road networks. In: Data and knowledge engineering, special issue with selected papers from the 8th international conference on enterprise information systems (ICEIS)
Stojanovic D, Papadopoulos AN, Predic B, Djordjevic-Kajan S, Nanopoulos A (2008) Continuous range monitoring of mobile objects in road networks. Data Knowl Eng (Jan):77–100
Tao Y, Papadias D, Sun J (2003) The TPR*-Tree: an optimized spatio-temporal access method for predictive queries. In: VLDB, pp 790–801
Trajcevski G, Wolfson O, Hinrichs K, Chamberlain S (2004) Managing uncertainty in moving objects databases. ACM Trans Database Syst 29(3):463–507
Wang H, Zimmermann R, Ku W-S (2006) Distributed continuous range query processing on moving objects. In: DEXA, pp 655–665
Wolfson O, Jiang L, Sistla AP, Chamberlain S, Rishe N, Deng M (1999) Databases for tracking mobile units in real time. In: Proceedings of the 7th international conference on database theory, January 10–12, 1999, Lecture notes in computer science, vol 1540. Springer, London, pp 169–186
Wolfson O, Sistla AP, Chamberlain S, Yesha Y (1999) Updating and querying databases that track mobile units. Distrib Parallel Databases 7(3):257–387
Wolfson O, Chamberlain S, Kalpakis K, Yesha Y (2002) Modeling moving objects for location based services. In: Revised papers from the NSF workshop on developing an infrastructure for mobile and wireless systems. Lecture notes in computer science, vol 2538. Springer, London, pp 46–58
Wong CY, Ibrahim H, Udzir NI (2008) Distributed real-time processing of range-monitoring queries in heterogeneous mobile databases. In: ICCIT, pp 74–81
Yu X, Pu KQ, Koudas N (2005) Monitoring k-nearest neighbor queries over moving objects. In: Proc ICDE
Zhang J, Zhu M, Papadias D, Tao Y, Lee DL (2003) Location-based spatial queries. In: Proc SIGMOD
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Cazalas, J., Guha, R. Leveraging computation sharing and parallel processing in location-dependent query processing. J Supercomput 61, 215–234 (2012). https://doi.org/10.1007/s11227-011-0651-z
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DOI: https://doi.org/10.1007/s11227-011-0651-z