Using quantitative analysis to implement autonomic IT systems

The software underpinning today's IT systems needs to adapt dynamically and predictably to rapid changes in system workload, environment and objectives. We describe a software framework that achieves such adaptiveness for IT systems whose components can be modelled as Markov chains. The framewo...

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Veröffentlicht in:	2009 IEEE 31st International Conference on Software Engineering S. 100 - 110
Hauptverfasser:	Calinescu, Radu, Kwiatkowska, Marta
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	Washington, DC, USA IEEE Computer Society 16.05.2009 IEEE
Schriftenreihe:	ACM Conferences
Schlagworte:	Computer architecture Computing methodologies > Modeling and simulation > Model development and analysis > Modeling methodologies Disk drives Energy consumption Energy management Knowledge management Logic devices Mathematics of computing > Probability and statistics > Probabilistic representations > Markov networks Mathematics of computing > Probability and statistics > Stochastic processes > Markov processes Pervasive computing Power system management Probabilistic logic Runtime Software and its engineering > Software creation and management > Designing software > Software implementation planning > Software design techniques Software and its engineering > Software creation and management > Software development process management Theory of computation > Theory and algorithms for application domains > Machine learning theory > Markov decision processes
ISBN:	9781424434534, 142443453X
ISSN:	0270-5257
Online-Zugang:	Volltext
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