Carnegie Mellon University
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Improving Architecture-Based Self-Adaptation Through Resource Prediction

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journal contribution
posted on 2011-11-01, 00:00 authored by Shang-Wen Cheng, Vahe V Poladian, David Garlan, Bradley Schmerl
An increasingly important concern for modern systems design is how best to incorporate self-adaptation into systems so as to improve their ability to dynamically respond to faults, resource variation, and changing user needs. One promising approach is to use architectural models as a basis for monitoring, problem detection, and repair selection. While this approach has been shown to yield positive results, current systems use a reactive approach: they respond to problems only when they occur. In this paper we argue that self-adaptation can be improved by adopting an anticipatory approach in which predictions are used to inform adaptation strategies. We show how such an approach can be incorporated into an architecture-based adaptation framework and demonstrate the benefits of the approach.


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