IJMECS Vol. 11, No. 6, 8 Jun. 2019
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Self-Adaptation, linear regression, environmental variant, design pattern, reusability, software variant, load balancer
Self-adaptive systems appeared in order to reduce the effort of manual software maintenance. Apart from software attributes, for example, different alternative software modules, self-adaptation decisions depend on environmental attributes, for example, service rate, bandwidth etc. Current well-known self-adaptation approaches can be further improved by incorporating environmental attributes. Moreover, reducing maintenance effort includes minimizing both operational and development effort. To reduce the effort of developing self-adaptive software, the constituent components should be reusable. This paper proposes a technique to incorporate environmental attributes to learning-based self-adaptation and to increase the reuse potential of self-adaptive system components. The environmental attributes are provided as a constraint to an optimization problem which results in an optimal software attribute selection. Design patterns for self-adaptive system components are proposed to improve its reusability. The proposed technique was validated on a news serving website called Znn.com. According to renowned reusability metrics such as Lines of Code (LOC), Message Passing Coupling (MPC) and Lack of Cohesion of Methods 4 (LCOM4), the proposed technique improved reuse potential. The website was further tested for adaptation effectiveness under two scenarios – adaptation and without adaptation. According to our experiments, Adaptation gradually improved the main goal response time of the website where it performed poorly without adaptation.
Kishan Kumar Ganguly, Md. Saeed Siddik, Rayhanul Islam, Kazi Sakib, "An Environment Aware Learning-based Self-Adaptation Technique with Reusable Components", International Journal of Modern Education and Computer Science(IJMECS), Vol.11, No.6, pp. 53-64, 2019.DOI: 10.5815/ijmecs.2019.06.06
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