DagRep.5.1.164.pdf
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Model-driven Algorithms and Architectures for Self-Aware Computing Systems (Dagstuhl Seminar 15041)
Authors and all authors of the abstracts in this report
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Issue:
Dagstuhl Reports, Volume 5, Issue 1
Volume: Dagstuhl Reports, Volume 5
Journal: Dagstuhl Reports (DagRep) - License:
Creative Commons Attribution 3.0 Unported license
- Publication Date: 2015-05-18
Cite AsGet BibTex
Samuel Kounev, Xiaoyun Zhu, Jeffrey O. Kephart, and Marta Kwiatkowska. Model-driven Algorithms and Architectures for Self-Aware Computing Systems (Dagstuhl Seminar 15041). In Dagstuhl Reports, Volume 5, Issue 1, pp. 164-196, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)
https://doi.org/10.4230/DagRep.5.1.164
https://doi.org/10.4230/DagRep.5.1.164
Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 15041 "Model-driven Algorithms and Architectures for Self-Aware Computing Systems". The design of self-aware computing systems calls for an integrated interdisciplinary approach building on results from multiple areas of computer science and engineering, including software and systems engineering, systems modeling, simulation and analysis, autonomic and organic computing, machine learning and artificial intelligence, data center resource management, and so on. The Dagstuhl Seminar 15041 served as a platform to raise the awareness about the relevant research efforts in the respective research communities as well as existing synergies that can be exploited to advance the state-of-the-art, formulate a new research agenda that takes a broader view on the problem following an integrated and interdisciplinary approach, and establish collaborations between academia and industry.
Keywords
- autonomic systems
- self-adaptive
- self-managing
- model-driven
- architecture-based
- systems management
- machine learning
- feedback-based design
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