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A. Gambi, M. Pezzè, G. Toffetti:
"Kriging-Based Self-Adaptive Cloud Controllers";
IEEE Transactions on Services Computing, Volume 9 (2016), Issue 3; 368 - 381.

Cloud technology is rapidly substituting classic computing solutions, and challenges the community with new problems. In this paper we focus on controllers for cloud application elasticity, and propose a novel solution for self-adaptive cloud controllers based on Kriging models. Cloud controllers are application specific schedulers that allocate resources to applications running in the cloud, aiming to meet the quality of service requirements while optimizing the execution costs. General-purpose cloud resource schedulers provide sub-optimal solutions to the problem with respect to application-specific solutions that we call cloud controllers. In this paper we discuss a general way to design self-adaptive cloud controllers based on Kriging models. We present Kriging models, and show how they can be used for building efficient controllers thanks to their unique characteristics. We report experimental data that confirm the suitability of Kriging models to support efficient cloud control and open the way to the development of a new generation of cloud controllers.

Self-adaptive controllers, cloud computing, IaaS, Kriging models

http://dx.doi.org/10.1109/TSC.2015.2389236