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Award Abstract #0325459
ITR: Collaborative Research: A Data Mining and Exploration Middleware for Grid and Distributed Computing


NSF Org: CCF
Division of Computer and Communication Foundations
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Initial Amendment Date: October 30, 2003
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Latest Amendment Date: October 26, 2006
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Award Number: 0325459
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Award Instrument: Continuing grant
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Program Manager: Almadena Y. Chtchelkanova
CCF Division of Computer and Communication Foundations
CSE Directorate for Computer & Information Science & Engineering
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Start Date: November 1, 2003
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Expires: October 31, 2008 (Estimated)
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Awarded Amount to Date: $535000
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Investigator(s): Sanjay Ranka ranka@cise.ufl.edu (Principal Investigator)
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Sponsor: University of Florida
1 UNIVERSITY OF FLORIDA
GAINESVILLE, FL 32611 352/392-3516
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NSF Program(s): ITR MEDIUM (GROUP) GRANTS
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Field Application(s): 0000099 Other Applications NEC
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Program Reference Code(s): HPCC, 9216, 1652
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Program Element Code(s): 1687

ABSTRACT



The purpose of this project is to develop and implement a middleware that allows mining and analysis of distributed data. The research will address an increasing interest in the exploration and mining of the large volume of data that is generated by the business, scientific, engineering, academic and defense communities.

Novel techniques will be developed in the following areas:

Data and Policy Management Services: These services will provide organizational level access restriction capabilities for the owners of the data while allowing users to access a more efficient transport of data.

Data Mining and Exploration Services: This framework will include a library of data mining tools that will work effectively for example if: data is distributed on multiple sites, the user has varying privileges depending on what site they are accessing, a user wants to trade off computing time versus accuracy or a user wants to access the site remotely.

Scheduling and Replication Services: System administration will be based upon policies at the participating organizations and their established privileges for users. Computation and data will be scheduled jointly to optimize metrics.

This combination of distributed computing and data mining will be made widely available to students, researchers, and other interested groups in government, industry and education.


PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Chitnis, L; Dobra, A; Ranka, S. "Aggregation methods for large-scale sensor networks," ACM TRANSACTIONS ON SENSOR NETWORKS, v.4, 2008. 

Jaeyeon Kang and Sanjay Ranka. "Energy-Efficient Dynamic Scheduling on Parallel Machines," HiPC 2008, 2008, p. 208.

Jang-uk In, Paul Avery, Richard Cavanaugh, Laukik Chitnis, Mandar Kulkarni, and Sanjay Ranka,. "SPHINX: A fault-tolerant system for scheduling in dynamic grid environments," Proceedings of the19th IEEE International Parallel & Distributed Processing Symposium, IPDPS 2005, 2005, p. 12.

Jang-uk In, Paul Avery, Richard Cavanaugh, Laukik Chitnis, Mandar Kulkarni, Pradeep Padala, and Sanjay Ranka. "SPHINX: A Scheduling Middleware for Data Intensive Applications on a Grid," Proceedings of Computing in High Energy Physics (CHEP 2004), 2004.

Jun Liu, Jaaved Mohammed , James Carter , Sanjay Ranka , Tamer Kahveci, and Michael Baudis. "Distance-based clustering of CGH data," Bioinformatics, v.22(16), 2006, p. 1971-1978.

Jun Liu, Jaaved Mohammed , James Carter , Sanjay Ranka , Tamer Kahveci, and Michael Baudis. "Distance-based clustering of CGH data," Bioinformatics, v.22(16), 2006, p. 1971?1978.

Jung, ES; Li, Y; Ranka, S; Sahni, S. "Performance Evaluation of Routing and Wavelength Assignment Algorithms For Optical Networks," 2008 IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATIONS, VOLS 1-3, 2008, p. 976-981. 

Kang, J; Ranka, S. "Dynamic algorithms for energy minimization on parallel machines," PROCEEDINGS OF THE 16TH EUROMICRO CONFERENCE ON PARALLEL, DISTRIBUTED AND NETWORK-BASED PROCESSING, 2007, p. 399-406. 

Kang, J; Ranka, S. "DVS based energy minimization algorithm for parallel machines," 2008 IEEE INTERNATIONAL SYMPOSIUM ON PARALLEL & DISTRIBUTED PROCESSING, VOLS 1-8, 2008, p. 1969-1980. 

Laukik Chitnis, Alin Dobra, and Sanjay Ranka. "Analyzing the multiple aggregation trees technique for fault tolerance in sensor networks," Proc. of International Conference on Information Systems, Technology and Management (ICISTM, 2007.


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Last Updated:April 2, 2007