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2013 8th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS) (2013)
San Francisco, CA, USA
May 20, 2013 to May 21, 2013
ISSN: 2157-2305
ISBN: 978-1-4799-0344-3
pp: 33-42
Alessio Gambi , Distributed Systems Group, Vienna University of Technology, Austria
Daniel Moldovan , Distributed Systems Group, Vienna University of Technology, Austria
Georgiana Copil , Distributed Systems Group, Vienna University of Technology, Austria
Hong-Linh Truong , Distributed Systems Group, Vienna University of Technology, Austria
Schahram Dustdar , Distributed Systems Group, Vienna University of Technology, Austria
ABSTRACT
Elastic controllers autonomically adjust the allocation of resources in cloud computing systems. Usually such controllers assume that control actions will take immediate effect. In clouds, however, actuation times may be long, and the controllers can hardly guarantee acceptable levels of service if they neglect these actuation delays. Therefore, the ability to correctly estimate the time that control actions take effect on the systems is crucial. However, detecting actuation delays in elastic computing systems is challenging because cloud systems provide only inaccurate and incomplete data about reconfigurations timing. In this paper, we tackle the problem of estimating the delay of control actions in elastic systems. We identify recurring types of changes in the monitored metrics and requirements to properly carry out the estimation. Based on that, we develop a novel framework for the actuation delays estimation that utilizes change point detection techniques. We conduct several experiments with real-world systems to illustrate the feasibility and applicability of our framework.
INDEX TERMS
Estimation, Monitoring, Delay estimation, Algorithm design and analysis, Virtual machining
CITATION

A. Gambi, D. Moldovan, G. Copil, H. Truong and S. Dustdar, "On estimating actuation delays in elastic computing systems," 2013 8th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), San Francisco, CA, USA, 2013, pp. 33-42.
doi:10.1109/SEAMS.2013.6595490
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