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

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Abstract

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.

Item Type:	Article
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Divisions:	School of Computing
Depositing User:	Dr. Massudi Mahmuddin
Date Deposited:	17 May 2015 07:57
Last Modified:	19 May 2016 04:27
URI:	https://repo.uum.edu.my/id/eprint/14186

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