TY - JOUR
T1 - Supporting performance awareness in autonomous ensembles
AU - Bulej, Lubomír
AU - Bureš, Tomáš
AU - Gerostathopoulos, Ilias
AU - Horký, Vojtéch
AU - Keznikl, Jaroslav
AU - Marek, Lukáš
AU - Tschaikowski, Max
AU - Tribastone, Mirco
AU - Tůma, Petr
PY - 2015/1/1
Y1 - 2015/1/1
N2 - The ASCENS project works with systems of self-aware, selfadaptive and self-expressive ensembles. Performance awareness represents a concern that cuts across multiple aspects of such systems, from the techniques to acquire performance information by monitoring, to the methods of incorporating such information into the design making and decision making processes. This chapter provides an overview of five project contributions - performance monitoring based on the DiSL instrumentation framework, measurement evaluation using the SPL formalism, performance modeling with fluid semantics, adaptation with DEECo and design with IRM-SA - all in the context of the cloud case study.
AB - The ASCENS project works with systems of self-aware, selfadaptive and self-expressive ensembles. Performance awareness represents a concern that cuts across multiple aspects of such systems, from the techniques to acquire performance information by monitoring, to the methods of incorporating such information into the design making and decision making processes. This chapter provides an overview of five project contributions - performance monitoring based on the DiSL instrumentation framework, measurement evaluation using the SPL formalism, performance modeling with fluid semantics, adaptation with DEECo and design with IRM-SA - all in the context of the cloud case study.
KW - Adaptive systems
KW - Autonomic Systems
KW - Modeling
KW - Monitoring
KW - Performance
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UR - http://www.scopus.com/inward/citedby.url?scp=84924358557&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:84924358557
SN - 0302-9743
VL - 8998
SP - 291
EP - 322
JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -