@InBook{Prediction2008,
AUTHOR = {Poladian, Vahe and Cheng, Shang-Wen and Garlan, David and Schmerl, Bradley},
TITLE = {Improving Architecture-Based Self-Adaption Through Resource Prediction},
YEAR = {2008},
BOOKTITLE = {Software Engineering for Self-Adaptive Systems},
VOLUME = {5525},
EDITOR = {Cheng, Betty H.C. and de Lemos, Rog\'{e}rio and Giese, Holger and Inverardi, Paola and Magee, Jeff},
SERIES = {Lecture Notes in Computer Science},
PUBLISHER = {LNCS},
CHAPTER = {15},
PDF = {http://acme.able.cs.cmu.edu/pubs/uploads/pdf/LNCS-SEfSASChapter-2009-0222-web.pdf},
ABSTRACT = {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.},
KEYWORDS = {Rainbow, Resource prediction, Self-adaptation}
}
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