| NSF Org: |
CCF Division of Computing and Communication Foundations |
| Recipient: |
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| Initial Amendment Date: | July 22, 2008 |
| Latest Amendment Date: | July 16, 2014 |
| Award Number: | 0811457 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Almadena Chtchelkanova
achtchel@nsf.gov (703)292-7498 CCF Division of Computing and Communication Foundations CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | August 1, 2008 |
| End Date: | September 30, 2014 (Estimated) |
| Total Intended Award Amount: | $250,000.00 |
| Total Awarded Amount to Date: | $250,000.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
202 HIMES HALL BATON ROUGE LA US 70803-0001 (225)578-2760 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
202 HIMES HALL BATON ROUGE LA US 70803-0001 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): |
COMPILERS, EPSCoR Co-Funding |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
Data protection and recovery have become increasing important as business, education, and government depend more and more on digital information.
Failure events do occur such as virus attacks, user errors, defective software/firmware, hardware faults, and site failures etc that cause data damage. To ensure business continuity and minimize loss, data storage systems need data protection and recovery techniques. However, existing technologies have severe limitations and unable to recover data in many situations. This project aims at studying and understanding how data recovery is done in existing data storage systems, and designing new architectures that will overcome the limitations of existing technologies.
In order to study and understand the existing storage architectures, a new mathematical formulation will be developed to model and analyze capabilities and limitations of the storage architectures. This mathematical model provides a rigorous tool for researchers and practitioners to investigate and understand storage system architectures.
Based on the new mathematical model, a class of new data storage system architectures will be designed that will have the maximum data recoverability. The new storage architectures make it possible for organizations of different sizes to have a cost-effective data storage that provides high data availability and allows quick data recovery upon failures. In addition to the theoretical study, experimental prototypes will be developed and implemented to demonstrate the feasibility, performance, reliability, and data recoverability of newly designed storage architectures. Furthermore, the project includes an education component that advocates a shift of emphasis from CPU-centric computer engineering (CE) curriculum to data-centric CE curriculum. The new curriculum provides CE students with in depth knowledge of data processing, data communication, and data storage.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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