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Using data mining to predict and generate optimum multiple execution paths compositions

In multiple execution paths compositions, can we generate solutions that simultaneously optimize all the execution paths, while meeting global QoS constraints imposed by the clients? This paper proposes a runtime path prediction method based on data mining techniqes. The method predicts, at runtime,...

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Main Authors: Mahmuddin, Massudi, Qtaish, Osama K., Jamaludin, Zulikha
Format: Article
Published: Software Engineering Competence Center (SECC) of Information Technology Industry Development Agency (ITIDA). 2014
Subjects:
QA76 Computer software
Online Access:http://repo.uum.edu.my/14186/
http://ijse.org.eg/issues/vol-7-no-1/
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spelling my.uum.repo.141862016-05-19T04:27:00Z http://repo.uum.edu.my/14186/ Using data mining to predict and generate optimum multiple execution paths compositions Mahmuddin, Massudi Qtaish, Osama K. Jamaludin, Zulikha QA76 Computer software In multiple execution paths compositions, can we generate solutions that simultaneously optimize all the execution paths, while meeting global QoS constraints imposed by the clients? This paper proposes a runtime path prediction method based on data mining techniqes. The method predicts, at runtime, the execution path that will be followed during the composition’s execution based on the information provided by composition requesters, making it possible to compute the optimization by considering only the predicted path. By using our method, it is expected to generate solutions that deliver the best possible QoS ratio, at the same time, minimize the violation of the global constraints. The proposed method is evaluated in terms of its prediction accuracy and scalability. Software Engineering Competence Center (SECC) of Information Technology Industry Development Agency (ITIDA). 2014-01 Article PeerReviewed Mahmuddin, Massudi and Qtaish, Osama K. and Jamaludin, Zulikha (2014) Using data mining to predict and generate optimum multiple execution paths compositions. International Journal of Software Engineering (IJSE), 7 (1). pp. 19-40. ISSN 1687-6954 http://ijse.org.eg/issues/vol-7-no-1/
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutionali Repository
url_provider http://repo.uum.edu.my/
topic QA76 Computer software
spellingShingle QA76 Computer software
Mahmuddin, Massudi
Qtaish, Osama K.
Jamaludin, Zulikha
Using data mining to predict and generate optimum multiple execution paths compositions
description In multiple execution paths compositions, can we generate solutions that simultaneously optimize all the execution paths, while meeting global QoS constraints imposed by the clients? This paper proposes a runtime path prediction method based on data mining techniqes. The method predicts, at runtime, the execution path that will be followed during the composition’s execution based on the information provided by composition requesters, making it possible to compute the optimization by considering only the predicted path. By using our method, it is expected to generate solutions that deliver the best possible QoS ratio, at the same time, minimize the violation of the global constraints. The proposed method is evaluated in terms of its prediction accuracy and scalability.
format Article
author Mahmuddin, Massudi
Qtaish, Osama K.
Jamaludin, Zulikha
author_facet Mahmuddin, Massudi
Qtaish, Osama K.
Jamaludin, Zulikha
author_sort Mahmuddin, Massudi
title Using data mining to predict and generate optimum multiple execution paths compositions
title_short Using data mining to predict and generate optimum multiple execution paths compositions
title_full Using data mining to predict and generate optimum multiple execution paths compositions
title_fullStr Using data mining to predict and generate optimum multiple execution paths compositions
title_full_unstemmed Using data mining to predict and generate optimum multiple execution paths compositions
title_sort using data mining to predict and generate optimum multiple execution paths compositions
publisher Software Engineering Competence Center (SECC) of Information Technology Industry Development Agency (ITIDA).
publishDate 2014
url http://repo.uum.edu.my/14186/
http://ijse.org.eg/issues/vol-7-no-1/
_version_ 1644281384217346048
score 13.211869

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