An Environment Aware Learning-based SelfAdaptation Technique with Reusable Components

Kishan Kumar Ganguly, Institute of Information Technology, University of Dhaka, Md. Saeed Siddik, Rayhanul Islam, Kazi Sakib
<span title="2019-06-08">2019</span> <i title="MECS Publisher"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/e2edi7vsvnbf3nx6iy25ioadxe" style="color: black;">International Journal of Modern Education and Computer Science</a> </i> &nbsp;
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
more &raquo; ... uce 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.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5815/ijmecs.2019.06.06">doi:10.5815/ijmecs.2019.06.06</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/a5ocl3xkunehbgg4cc7hntfwk4">fatcat:a5ocl3xkunehbgg4cc7hntfwk4</a> </span>
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