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@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}
}
    Created: 2008-10-03 16:35:40     Modified: 2012-07-23 11:00:43
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