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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Format: | Article |
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Software Engineering Competence Center (SECC) of Information Technology Industry Development Agency (ITIDA).
2014
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author | Mahmuddin, Massudi Qtaish, Osama K. Jamaludin, Zulikha |
author_facet | Mahmuddin, Massudi Qtaish, Osama K. Jamaludin, Zulikha |
author_sort | Mahmuddin, Massudi |
collection | UUM |
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. |
first_indexed | 2024-07-04T05:54:59Z |
format | Article |
id | uum-14186 |
institution | Universiti Utara Malaysia |
last_indexed | 2024-07-04T05:54:59Z |
publishDate | 2014 |
publisher | Software Engineering Competence Center (SECC) of Information Technology Industry Development Agency (ITIDA). |
record_format | eprints |
spelling | uum-141862016-05-19T04:27:00Z https://repo.uum.edu.my/id/eprint/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/ |
spellingShingle | QA76 Computer software Mahmuddin, Massudi Qtaish, Osama K. Jamaludin, Zulikha Using data mining to predict and generate optimum multiple execution paths compositions |
title | 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_short | 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 |
topic | QA76 Computer software |
work_keys_str_mv | AT mahmuddinmassudi usingdataminingtopredictandgenerateoptimummultipleexecutionpathscompositions AT qtaishosamak usingdataminingtopredictandgenerateoptimummultipleexecutionpathscompositions AT jamaludinzulikha usingdataminingtopredictandgenerateoptimummultipleexecutionpathscompositions |