Principles and Implementation Techniques for the Recovery   Component of a DBMS (Computer and Information Science)
{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}
{'SignBlockName': 'MICHELE R. JOHNSON', 'PO_EMAI': None, 'PO_PHON': None}
This research investigates the limits of transaction system             performance on computer systems with a high degree of                           parallelism.  The performance of a database management system is                dominated by its recovery component. The proposed work will                     address methods of minimizing the time taken by the recovery                    component of a database management system. The methods to be                    investigated are of two types: one type is the use of                           "non-blocking" methods of guaranteeing recoverability.  The other               type uses knowledge of transaction semantics, including the                     implementation of concurrency control and recovery separately for               different levels of abstraction.                                                        The importance of this work is that many industries such as             banks, financial markets, and reservation systems are making                    heavy use of large-scale shared databases.  The databases that                  make this possible must be updated quickly and correctly, even                  when many customers are accessing the same data.  Also, the                     shared databases must function reliably, even when some of the                  computer components fail. The research conducted here will lead                 to reducing the time required to reliably process a request,                    below the time required by present day state-of-the-art systems.
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{'Name': 'Georgia Tech Research Corporation', 'CityName': 'ATLANTA', 'ZipCode': '303186395', 'PhoneNumber': '4048944819', 'StreetAddress': '926 DALNEY ST NW', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Georgia', 'StateCode': 'GA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'GA05', 'ORG_UEI_NUM': 'EMW9FC8J3HN4', 'ORG_LGL_BUS_NAME': 'GEORGIA TECH RESEARCH CORP', 'ORG_PRNT_UEI_NUM': 'EMW9FC8J3HN4'}
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{'Code': '6856', 'Text': 'ARTIFICIAL INTELL & COGNIT SCI'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1986&All=true', 'xml': '8619281.xml'}