QUERY MELTING - A New Paradigm for GIS Multiple Query Optimization

Haifa Elsidani Elariss, Souheil Khaddaj, Darrel Greenhill

2009

Abstract

Recently, non-expert mobile-user applications have been developed to query Geographic Information Systems (GIS) particularly Location Based Services where users ask questions related to their position whether they are moving (dynamic) or not (static). A new Iconic Visual Query Language (IVQL) has been developed to handle proximity analysis queries that find k-nearest-neighbours and objects within a buffer area. Each operator in IVQL queries corresponds to an execution plan to be evaluated by the GIS server. Since commonalities exist between the execution plans, the same operations are executed many times leading to slow results. Hence, the need arises to develop a multi-user dynamic complex query optimizer that handles commonalities and processes the queries faster especially with the large-scale of mobile-users. We present a new query processor, a generic optimization framework for GIS and a middleware, which employs the new Query Melting paradigm (QM) that is based on the sharing paradigm and push-down optimization strategy. QM is implemented through a new Melting-Ruler strategy that works at the low-level, melts repetitions in plans to share spatial areas, temporal intervals, objects, intermediate results, maps, user locations, and functions, then re-orders them to get time-cost effective results, and is illustrated using a sample tourist GIS system.

References

  1. Afework A., Beynon M. D., Bustamante F., Demarzo A., Ferreira R., Miller R., Silberman M., Saltz J., Sussman A., and Tsang H., 1998. Digital Dynamic Telepathology - The Virtual Microscope, In AMIA 98, American Medical Informatics Association, 1998.
  2. Andrade H., Kurc T., Sussman A., and Saltz J., 2001. Efficient Execution of Multiple Query Workloads in Data Analysis Applications. Proceedings of SC2001, Denver, USA.
  3. Andrade H., Kurc T., Sussman A., Borovikov E., and Saltz J., 2002a. On Cache Replacement Policies for Servicing Mixed Data Intensive Query Workload. Proceedings of the 2nd Workshop on Caching, Coherence, and Consistency, 2002.
  4. Andrade H., Kurc T., Sussman A., and Saltz J., 2002b, Scheduling Multiple Data Visualization Query Workloads on a Shared Memory Machine, Proceedings of the 2002 International Parallel and Distributed Processing, 2002.
  5. Andrade H., Kurc T., Sussman A., and Saltz J., 2002c, Multiple Query Optimization for Data Analysis Applications on Clusters of SMPs, In Proceedings of the 2nd International Symposium on Cluster Computing and the Grid, 2002.
  6. Andrade H., Kurc T., Sussman A., and Saltz J., 2002d, Active Proxy-G: Optimizing the Query Execution Process in the Grid, Proceedings of the 2002 ACM/IEEE Supercomputing Conference, 2002.
  7. Andrade H., Kurc T., Sussman A., and Saltz J., 2002e, Processing Large-Scale Multi-dimensional Data in Parallel and Distributed Environments, Parallel Computing, 28(5), 827-859, 2002.
  8. Andrade H., Aryangat S., Kurc T., Slatz J., and Sussman A., 2003, Efficient Execution of Multi-Query Data Analysis Batches Using Compiler Optimization Strategies, Proceedings of the 16th International Workshop on Compilers for Computing, LCPC, 2003.
  9. Andrade H., Kurc T., Sussman A., and Beomseok N., 2006, Data Management and Query - Multiple Range Query Optimization with Distributed Cache Indexing, SIGMOD Conference, 2006.
  10. Andrienko G., Andrienko N., and Wrobel S., 2007, Visual Analytics tools for Analysis of Movement Data, In Proceedings of ACM SIGKDD Explorations Newsletter, Vol. (9) 2, ACM.
  11. Beeharee A., and Steed A., 2006, A Natural Wayfinding Exploiting Photos in Pedestrian Navigation Systems, In Proceedings on Human-computer Interaction with Mobile Devices and Services, MobileHCI'06.
  12. Beeharee A., and Steed A., 2007, Exploiting Real World Knowledge in Ubiquitous Applications, Personal and Ubiquitous Computing.
  13. Elmongui H., Mokbel M., and Aref W., 2005, Spatiotemporal Histograms, Proceedings of SSTD, 2005.
  14. Elmongui H., Ouzzani M., and Aref W., 2006, Challenges in Spatio-temporal Stream Query Optimization. Proceedings of MobiDE 2006, Chicago.
  15. Elsidani Elariss H., Khaddaj S., and Haraty R., 2006a, Towards a New Visual Query Language for GIS. IASTED Databases and Applications 2006, 195-202, Austria 2006.
  16. Elsidani Elariss H., Khaddaj S., and Haraty R., 2006b, An Evaluation of a Visual Query Language for Information Systems. ICEIS (5) 2006, 51-58, Paphos.
  17. Gianotti F., Nanni M., Pinelli F., and Pedreschi D., 2007, Trajectory Pattern Mining, In Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD'07.
  18. Guting H., De Almeida T., and Ding Z., 2006, Modeling and Querying Moving Objects in Networks, VLDB Journal - The International Journal on Very Large Databases, Vol. (15) 2.
  19. Kang M., Dietz H., and Bhargava B., 1994, MultipleQuery Optimization at Algorithm-Level. Proceedings of SSDI 1994, Data Engineering 14, 57-75.
  20. Kim S., Diverdi S., Chang J., Kang T., Iltis R., and Hollerer T., 2007, Implicit 3D Modeling and Tracking for Anywhere Augmentation, VRST 2007, Newport Beach, California, November 5-7, 2007.
  21. Ladd A., Bekris K., Rudys A., Kavraki L., and Wallach D., 2005, Robotics-Based Location Sensing Using Wireless Ethernet, Proceedings of the 8th ACM International Conference on Mobile Computing and Networking, MOBICOM, Sep. 2002, Atlanta, GA.
  22. Mokbel M.F., Aref W.G., Hambrush S.E., and Prabhakar S., 2003, Towards Scalable Location-Aware Services: Requirements and Reseach Issues. In Proceedings of the ACM Symposium on Advances in Geographical Information Systems, ACM GIS.
  23. Mokbel M.F., Xiong X., Aref W.G., Hambrush S.E., and Prabhakar S., Hammad M., , 2004a, PLACE: A Query Processor for Handling Real-Time Spatio-temporal Data Streams. In Proceedings of the VLDB.
  24. Mokbel M.F., Xiong X., and Aref W.G., 2004b, SINA: Scalable Incremental Processing of Continuous Queries In Spatio-temporal Databases. In Proceedings of the SIGMOD.
  25. Mokbel M.F., 2004c, Continuous Query Processing in Spatio-temporal Databases. In Proceedings of the ICDE/EDBT PhD Workshop.
  26. Mokbel M.F., Xiong X., Hammad M., and Aref W.G., 2005a, Continuous Query Processing of Spatiotemporal Data Streams in PLACE. GeoInformatica, 9(4), 343-365, 2005.
  27. Mokbel M.F., and Aref W.G., 2005b, GPAC: Generic and Progressive Processing of Mobile Queries over Mobile Data. In Proceedings of the MDM, Aya Napa, Cyprus.
  28. Repenning A., and Ioannidou A., 2006, Mobility Agents: Guiding and Tracking Public Transportation Users, Proceedings of the Working Conference on Advanced Visual Interfaces, AVI'06.
  29. Xiong X., Mokbel M.F., Aref W.G., and Prabhakar S., 2004, Scalable Spatio-temporal Continuous Query Processing for Location Aware Services. In Proceedings of the International Conference on Scientific and Statistical Database Management.
Download


Paper Citation


in Harvard Style

Elsidani Elariss H., Khaddaj S. and Greenhill D. (2009). QUERY MELTING - A New Paradigm for GIS Multiple Query Optimization . In Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-8111-84-5, pages 82-90. DOI: 10.5220/0001960700820090


in Bibtex Style

@conference{iceis09,
author={Haifa Elsidani Elariss and Souheil Khaddaj and Darrel Greenhill},
title={QUERY MELTING - A New Paradigm for GIS Multiple Query Optimization},
booktitle={Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2009},
pages={82-90},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001960700820090},
isbn={978-989-8111-84-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - QUERY MELTING - A New Paradigm for GIS Multiple Query Optimization
SN - 978-989-8111-84-5
AU - Elsidani Elariss H.
AU - Khaddaj S.
AU - Greenhill D.
PY - 2009
SP - 82
EP - 90
DO - 10.5220/0001960700820090