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Article:A Regression-based Method for Software Performance Engineering

by Omid Bushehrian, Reza Ghanbari Baghnavi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 31 - Number 7
Year of Publication: 2011
Authors: Omid Bushehrian, Reza Ghanbari Baghnavi
10.5120/3840-5341

Omid Bushehrian, Reza Ghanbari Baghnavi . Article:A Regression-based Method for Software Performance Engineering. International Journal of Computer Applications. 31, 7 ( October 2011), 46-50. DOI=10.5120/3840-5341

@article{ 10.5120/3840-5341,
author = { Omid Bushehrian, Reza Ghanbari Baghnavi },
title = { Article:A Regression-based Method for Software Performance Engineering },
journal = { International Journal of Computer Applications },
issue_date = { October 2011 },
volume = { 31 },
number = { 7 },
month = { October },
year = { 2011 },
issn = { 0975-8887 },
pages = { 46-50 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume31/number7/3840-5341/ },
doi = { 10.5120/3840-5341 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:17:32.682522+05:30
%A Omid Bushehrian
%A Reza Ghanbari Baghnavi
%T Article:A Regression-based Method for Software Performance Engineering
%J International Journal of Computer Applications
%@ 0975-8887
%V 31
%N 7
%P 46-50
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper a statistical methodology for finding the optimal deployment of distributed software objects over computational nodes is presented. The optimal placement of a distributed software objects, from the performance viewpoint, has a significant impact on the performance of the software. In the proposed methodology, a performance predictor function is extracted from a dataset of simulation results using the regression analysis. This performance predictor function then is used by an optimization algorithm to find the optimal object deployment. The key advantage of the proposed methodology over using the traditional QN models is that solving the predictor model obtained from the QN approach during the optimization process many times, particularly when the search space is huge, is prohibiting due to its time complexity.

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Index Terms

Computer Science
Information Sciences

Keywords

Software Performance Engineering optimal object deployment simulation Finite State Process