A middleware for developing and deploying scalable remote mining services

Proceedings CCGRID 2008 - 8th IEEE International Symposium on Cluster Computing and the Grid

Volumn , Issue , 2008, Pages 242-249

  Glimcher, Leonid ^a   Agrawal, Gagan ^a  

^a Ohio State University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADMINISTRATIVE DATA PROCESSING; APPLICATIONS; CHLORINE COMPOUNDS; COMPUTER NETWORKS; COMPUTER SOFTWARE; DATA MINING; DATA STORAGE EQUIPMENT; DECISION SUPPORT SYSTEMS; DISTRIBUTED COMPUTER SYSTEMS; INFORMATION MANAGEMENT; MIDDLEWARE; MINING; SCALABILITY; TECHNICAL PRESENTATIONS;

CLUSTER COMPUTING; INTERNATIONAL SYMPOSIUM; REMOTE SERVERS; WEB SERVICES;

DATA PROCESSING;

EID: 50649118393     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CCGRID.2008.36     Document Type: Conference Paper

References (54)

1. DataGrid Project. http://eu-datagrid.org.
2. Distributed Applications and Middleware for Industrial Use of European Networks (DAMIEN). http://www.hlrs.de/organization/pds/projects/damien.
3. Earth System Grid-II. http://www.earthsystemgrid.org.
4. Grid Enabled Optimisation & DesIgn Search for Engineering (GEODISE). http://www.geodise.com.
5. GRIDS-Center Software Suite. http://www.grids-center.org.
6. SDSC Storage Resource Broker. http://www.sdsc.edu/srb.
7. WSRF::Lite - Perl Grid Services. http://www.sve.man.ac.uk/Research/AtoZ/ ILCT.
8. D. Abramson, J. Giddy, and L. Kotler. High performance parametric modeling with nimrod/G: Killer application for the global grid? In IPDPS, pages 520-528, 2000.
9. Gagan Agrawal and Joel Saltz. Interprocedural data flow based optimizations for distributed memory compilation. Software Practice and Experience, 1996. Accepted for Publication.
10. G. Allen, K. Davis, K. Dolkas, N. Doulamis, T. Goodale, T. Kielmann, A. Merzky, J. Nabrzyski, J. Pukacki, T. Radke, M. Russell, E. Seidel, J. Shalf, and I. Taylor. Enabling applications on the grid: A gridlab overview. In International Journal of High Performance Computing Applications, August 2003.
11. Gabrielle Allen, Werner Benger, Tom Goodale, Hans-Christian Hege, Gerd Lanfermann, Andre Merzky, Thomas Radke, Edward Seidel, and John Shalf. The cactus code: A problem solving environment for the grid. In HPDC, pages 253+, 2000.
12. Michael D. Beynon, Tahsin Kurc, Umit Catalyurek, Chialin Chang, Alan Sussman, and Joel Saltz. Distributed processing of very large datasets with DataCutter. Parallel Computing, 27(11):1457-1478, October 2001.
13. Karoly Bosa, Wolfgang Schreiner, Michael Buchberger, and Thomas Kaltofen. A Grid Software for Virtual Eye Surgery Based on Globus 4 and gLite. In IEEE Computer Society, editor, Proceedings of ISPDC 2007, pages -, 2007.
14. P. Brezany, J. Hofer, A. Tjoa, and A. Wohrer. Gridminer: An infrastructure for data mining on computational grids. In Proceedings of Australian Partnership for Advanced Computing Conference (APAC), Gold Coast, Australia, October 2003.
15. P. Cheeseman and J. Stutz. Bayesian classification (autoclass): Theory and practice. In Advanced in Knowledge Discovery and Data Mining, pages 61 - 83. AAAI Press / MIT Press, 1996.
16. A. Chervenak, I. Foster, C. Kesselman, C. Salisbusy, and S. Tuecke. The Data Grid: Towards An Architecture for the Distributed Management and Analysis of Large Scientific Datasets. Journal of Network and Computer Applications, 2001.
17. Antonio Congiusta, Domenico Talia, and Paolo Trunfio. Wsrf-based services for distributed data mining. In Domenico Talia, Angelos Bilas, and Marios D. Dikaiakos, editors, Knowledge and Data Management in Grids, pages 203-220. Springer, USA, 2007. ISBN 0-387-37830-8.
18. V. Curcin, M. Ghanem, Y. Guo, M. Kohler, A. Rowe, J. Syed, and P. Wendel. Grid knowledge discovery processes and an architecture for their composition. In The Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Edmonton, Alberta, Canada, July 2002.
19. K. Czajkowski, D. F. Ferguson, I. Foster, J. Frey, S. Graham, I. Sedukhin, D. Snelling, S. Tuecke, and W. Vambenepe. The WS-Resource Framework. March 5, 2004.
20. Arthur Dempster, Nan Laird, and Donald Rubin. Maximum Likelihood Estimation from Incomplete Data via the EM Algorithm. Journal of the Royal Statistical Society, 39(1):1-38, 1977.
21. Chris Ferris and Joel Farrell. What are Web Services. Communications of the ACM (CACM), pages 31-35, June 2003.
22. Ian Foster. Service-Oriented Science. Science, 308(5723):814-807, May 2005.
23. Ian Foster. Globus Toolkit Version 4: Software for Service-Oriented Systems. IFIP International Conference on Network on Parallel Computing, 2006.
24. Ian Foster, Carl Kesselman, Jeffrey M. Nick, and Steven Tuecke. The Physiology of the Grid: An Open Grid Services Architecture for Distributed Systems Integration. In Open Grid Service Infrastructure Working Group, Global Grid Forum, June 2002.
25. M. Ghanem, Y. Guo, A. Rowe, and P. Wendel. Grid-based knowledge discovery services for high throghput informatics. In The Eleventh IEEE International Symposium on High Performance Distributed Computing, Edinburgh, Scotland, July 2002.
26. Leo Glimcher and Gagan Agrawal. Parallelizing EM Clustering Algorithm on a Cluster of SMPs. In Proceedings of Europar, 2004.
27. Leo Glimcher and Gagan Agrawal. Performance of Remote Mining Applications With SRB-based Servers . In Proceedings of the International Parallel and Distributed Processing Symposium (IPDPS) (submitted for review), 2007.
28. Leo Glimcher, Ruoming Jin, and Gagan Agrawal. FREERIDE-G: Supporting Applications that Mine Data Repositories. In In proceedings of International Conference on Parallel Processing (ICPP), 2006.
29. Leo Glimcher, Xuan Zhang, and Gagan Agrawal. Scaling and Parallelizing a Scientific Feature Mining Application Using a Cluster Middleware. In Proceedings of the International Parallel and Distributed Processing Symposium (IPDPS), 2004.
30. Jiawei Han and Micheline Kamber. Data Mining: Concepts and Techniques. Morgan Kaufmann Publishers, 2000.
31. J. A. Hartigan and M. A. Wong. A k-means clustering algorithm. Applied Statistics, (28):100-108, 1979.
32. Yu'an He, Tao Yu, Lilan Liu, Bin Shen, and Haiyang Sun. A wsrfbased resource management system of manufacturing grid. In CCGRID '06: Proceedings of the Sixth IEEE International Symposium on Cluster Computing and the Grid (CCGRID'06), pages 174-177, Washington, DC, USA, 2006. IEEE Computer Society.
33. M. Humphrey, G. Wasson, K. Jackson, J. Boverhof, M. Rodriguez, J. Gawor, J. Bester, S. Lang, I. Foster, S. Meder, S. Pickles, and M. McKeown. State and events for web services: a comparison of five ws-resource framework and ws-notification implementations. In IEEE Computer Society, editor, 14th IEEE International Symposium on High Performance Distributed Computing, pages 3-13, 2005.
34. J. C. Jacob, R. Williams, J. Babu, S. G. Djorgovski, M. J. Graham, D. S. Katz, A. Mahabal, C. D. Miller, R. Nichol, D. E. Vanden Berk, and H. Walia. Grist: Grid data mining for astronomy. In Astronomical Data Analysis Software and Systems (ADASS) XIV, October 2004.
35. A. K. Jain and R. C. Dubes. Algorithms for Clustering Data. Prentice Hall, 1988.
36. Ivan Janciak, Peter Brezany, and A. Min Tjoa. Towards the Wisdom Grid: Goals and Architecture. In Proceedings of 4th International Conference on Parallel Processing and Applied Mathematics (PPAM), pages 796-803, 2003.
37. Ruoming Jin and Gagan Agrawal. Shared Memory Parallelization of Data Mining Algorithms: Techniques, Programming Interface, and Performance. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2005.
38. Nicholas T. Karonis and et al. Mpich-g2: A grid-enabled implementation of the message passing interface.
39. G. Kickinger, P.Brezany, A. Tjoa, and J. Hofer. Grid knowledge discovery processes and an architecture for their composition. In Proceedings of the IASTED International Conference on Parallel and Distributed Computing and Networks (PDCN 2004), Innsbruck, Austria, February 2004.
40. Donny Kurniawan and David Abramson. A wsrf-compliant debugger for grid applications. In 21st IEEE International Parallel and Distributed Processing Symposium, pages 2-13, 2007.
41. R. Machiraju, J. Fowler, D. Thompson, B. Soni, and W. Schroeder. EVITA - Efficient Visualization and Interrogation of Terascale Datasets. In et al R. L. Grossman, editor, Data Mining for Scientific and Engineering Applications, pages 257-279. Kluwer Academic Publishers, 2001.
42. M.Cannataro, A. Congiusta, A. Pugliese, D. Talia, and P. Trunfio. Distributed Data Mining on Grids: Services, Tools, and Applications. IEEE Transactions on Systems, Man and Cybernetics, Part B, 34(6):2451-2465, December 2004.
43. M.Cannataro and D. Talia. KNOWLEDGE GRID: An Architecture for Distributed Knowledge Discovery. Communications of the ACM, 46(1):89-93, January 2003.
44. S. K. Murthy. Automatic construction of decision trees from data: A multi-disciplinary survey. Data Mining and Knowledge Discovery, 2(4):345-389, 1998.
45. S. Narayanan, U. Catalyurek, T. Kurc, X. Zhang, and J. Saltz. Applying database support for large scale data driven science in distributed environments. In International Workshop on Grid Computing (Grid 2004), 2003.
46. Constantin Pistol and Anita Lungu. Deploying C++ Grid Services: Options and Performance. http://www.cs.duke.edu/anda/cps296.5/final_projects/PaperWS. pdf.
47. A. Shelestov, A. Lobunets, and M. Korbakov. Grid-Enabling Satellite Image Archive Prototype For UA Space Grid Testbed. International Journal on Information Theories and Applications, 12(4):351-358, March 2004.
48. Vlado Stankovski, Michael May, Jürgen Franke, Assaf Schuster, Damian McCourt, and Werner Dubitzky. A service-centric perspective for data mining in complex problem solving environments. In Proceedings of International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA), pages 780-787, 2004.
49. T. Friese and M. Smith and B. Freisleben. Grid Development Tools for Eclipse. http://www.sciences.univnantes.fr/lina/atl/www/papers/eTX2006/07- ThomasFriese.pdf.
50. D.S. Thompson, R. Machiraju, M. Jiang, V. S. Dusi, J. Nair, and G. Craciun. Physics-Based Mining of Computational Fluid Dynamics Datasets. IEEE Computational Science & Engineering, 4(3), 2002.
51. S Venugopal, R Buyya, and L. Winton. A grid based service broker for scheduling e-science applicaitons of global data grids. Journal of Concurrency and Computation: Practice and Experience, 18(6):685-699, 2005.
52. G. Wasson, N. Beekwilder, M. Morgan, and M. Humphrey. WS-ResourceFramework on .NET. http://csdl2.computer.org/comp/proceedings/hpdc/ 2004/2175/00/21750258.pdf.
53. Glenn Wasson and Marty Humphrey. Exploiting wsrf and wsrf.net for remote job execution in grid environments. In IPDPS '05: Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers, page 12.1, Washington, DC, USA, 2005. IEEE Computer Society.
54. Ming Zhao, V. Chadha, and R. J. Figueiredo. Supporting application-tailored grid file system sessions with wsrf-based services. In Proceedings. 14th IEEE International Symposium on High Performance Distributed Computing(HPDC-14), pages 24-33, 2005.