ATAC4Cloud: a framework for modeling and simulating autonomic cloud

ATAC4Cloud: a framework for modeling and simulating autonomic cloud Optimizing resources usage costs represents a key issue in order to efficiently manage Cloud infrastructure. By using such infrastructure, the ability to infer the needed number and type of resources determines the final budget. A lot of work and budget is required to set up a testbed of adequate size, including different resources from different Cloud providers, in order to develop new proposals aimed at Cloud resources adaptation. Several Cloud computing simulators including MDCSim, GreenCloud, iCanCloud and CloudSim have been proposed, but their main problems are that they don’t take into account Cloud self-adaptation needs. For these reasons, we propose in this paper ATAC4Cloud, a Cloud simulator supporting autonomic behaviors and integrating a workload generator that builds benchmarks to test the Cloud infrastructure. The underpinning of this work is the synergy existing between agent technology and autonomic computing to develop self-adaptive Cloud systems. ATAC4Cloud is developed as an extension of CloudSim. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Soft Computing Springer Journals

ATAC4Cloud: a framework for modeling and simulating autonomic cloud

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Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2016 by Springer-Verlag Berlin Heidelberg
Subject
Engineering; Computational Intelligence; Artificial Intelligence (incl. Robotics); Mathematical Logic and Foundations; Control, Robotics, Mechatronics
ISSN
1432-7643
eISSN
1433-7479
D.O.I.
10.1007/s00500-016-2451-0
Publisher site
See Article on Publisher Site

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