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An analytical model for evaluating database update schemes

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Date Issued:
1983
Abstract/Description:
University of Central Florida College of Arts and Sciences Thesis; A methodology is presented for evaluating the performance of database update schemes. The methodology uses the M/Hr/1 queueing model as a basis for this analysis and makes use of the history of how data is used in the database. Parameters have been introduced which can be set based on the characteristics of a specific system. These include update to retrieval ratio, average file size, overhead, block size and the expected number of items in the database. The analysis is specifically directed toward the support of derived data within the relational model. Three support methods are analyzed. These are first examined in a central database system. The analysis is then extended in order to measure performance in a distributed system. Because concurrency is a major problem in a distributive system, the support of derived data is analyzed with respect to three distributive concurrency control techniques -- master/slave, distributed and synchronized. In addition to its use as a performance predictor, the development of the methodology serves to demonstrate how queueing theory may be used to investigate other related database problems. This is an important benefit due to this lack of fundamental results in the area of using queueing theory to analyze database performance.
Title: An analytical model for evaluating database update schemes.
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Name(s): Kinsley, Kathryn C., Author
Hughes, Charles E., Committee Chair
Arts and Sciences, Degree Grantor
Type of Resource: text
Date Issued: 1983
Publisher: University of Central Florida
Language(s): English
Abstract/Description: University of Central Florida College of Arts and Sciences Thesis; A methodology is presented for evaluating the performance of database update schemes. The methodology uses the M/Hr/1 queueing model as a basis for this analysis and makes use of the history of how data is used in the database. Parameters have been introduced which can be set based on the characteristics of a specific system. These include update to retrieval ratio, average file size, overhead, block size and the expected number of items in the database. The analysis is specifically directed toward the support of derived data within the relational model. Three support methods are analyzed. These are first examined in a central database system. The analysis is then extended in order to measure performance in a distributed system. Because concurrency is a major problem in a distributive system, the support of derived data is analyzed with respect to three distributive concurrency control techniques -- master/slave, distributed and synchronized. In addition to its use as a performance predictor, the development of the methodology serves to demonstrate how queueing theory may be used to investigate other related database problems. This is an important benefit due to this lack of fundamental results in the area of using queueing theory to analyze database performance.
Identifier: CFR0011600 (IID), ucf:53041 (fedora)
Note(s): 1983-05-01
Ph.D.
Computer Science
Doctorate
This record was generated from author submitted information.
Electronically reproduced by the University of Central Florida from a book held in the John C. Hitt Library at the University of Central Florida, Orlando.
Subject(s): Database management
Electronic data processing -- Mathematical models
Persistent Link to This Record: http://purl.flvc.org/ucf/fd/CFR0011600
Restrictions on Access: public
Host Institution: UCF

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