Optimization of distributed, object-oriented architectures
Object-Oriented computing is fast becoming the de-facto standard for software development. Optimal deployment strategies for object servers change given variations in object servers, client applications, operational missions, hardware modifications, and various other changes to the environment. Once...
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ndltd-nps.edu-oai-calhoun.nps.edu-10945-97512014-11-27T16:08:33Z Optimization of distributed, object-oriented architectures Ray, William J. Berzins, Valdis Software Engineering Object-Oriented computing is fast becoming the de-facto standard for software development. Optimal deployment strategies for object servers change given variations in object servers, client applications, operational missions, hardware modifications, and various other changes to the environment. Once distributed object servers become more prevalent, there will be a need to optimize the deployment of object servers to best serve the end usergass changing needs. Having a system that automatically generates object server deployment strategies would allow users to take full advantage of their network of computers. Many systems have very predictable points in time where the usage of a network changes. These systems are usually characterized by shift changes where the manning and functions preformed change from shift to shift. We propose a pro-active optimization approach that uses predictable indicators like season, mission, and other foreseeable periodic events. The proposed method profiles object servers, client applications, user inputs and network resources. These profiles determine a system of equations that is solved to produce an optimal deployment strategy for the predicted upcoming usage by the users of the system of computers and servers. 2012-08-22T15:29:59Z 2012-08-22T15:29:59Z 2001-09 Thesis http://hdl.handle.net/10945/9751 This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. As such, it is in the public domain, and under the provisions of Title 17, United States Code, Section 105, it may not be copyrighted. |
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Object-Oriented computing is fast becoming the de-facto standard for software development. Optimal deployment strategies for object servers change given variations in object servers, client applications, operational missions, hardware modifications, and various other changes to the environment. Once distributed object servers become more prevalent, there will be a need to optimize the deployment of object servers to best serve the end usergass changing needs. Having a system that automatically generates object server deployment strategies would allow users to take full advantage of their network of computers. Many systems have very predictable points in time where the usage of a network changes. These systems are usually characterized by shift changes where the manning and functions preformed change from shift to shift. We propose a pro-active optimization approach that uses predictable indicators like season, mission, and other foreseeable periodic events. The proposed method profiles object servers, client applications, user inputs and network resources. These profiles determine a system of equations that is solved to produce an optimal deployment strategy for the predicted upcoming usage by the users of the system of computers and servers. |
author2 |
Berzins, Valdis |
author_facet |
Berzins, Valdis Ray, William J. |
author |
Ray, William J. |
spellingShingle |
Ray, William J. Optimization of distributed, object-oriented architectures |
author_sort |
Ray, William J. |
title |
Optimization of distributed, object-oriented architectures |
title_short |
Optimization of distributed, object-oriented architectures |
title_full |
Optimization of distributed, object-oriented architectures |
title_fullStr |
Optimization of distributed, object-oriented architectures |
title_full_unstemmed |
Optimization of distributed, object-oriented architectures |
title_sort |
optimization of distributed, object-oriented architectures |
publishDate |
2012 |
url |
http://hdl.handle.net/10945/9751 |
work_keys_str_mv |
AT raywilliamj optimizationofdistributedobjectorientedarchitectures |
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1716721422216200192 |