Analytical Modeling of Reactive Autonomic Management Techniques in IaaS Clouds

TitleAnalytical Modeling of Reactive Autonomic Management Techniques in IaaS Clouds
Publication TypeConference Proceedings
Year of Conference2015
AuthorsBruneo, D., F. Longo, R. Ghosh, M. Scarpa, A. Puliafito, and K. Trivedi
Conference NameProceedings - 2015 IEEE 8th International Conference on Cloud Computing, CLOUD 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Conference LocationNew York (USA)
ISBN Number9781467372879
KeywordsAutonomic management, cloud computing, Cloud computing infrastructures, Cloud infrastructures, Iaas clouds, Industrial management, Infrastructure as a service (IaaS), Performance metrics, Petri nets, Quality of service, Resiliency, Service Level Agreements, Stochastic reward nets, Stochastic systems

Cloud computing infrastructures provide services to a wide number of users whose behavior can deeply change at the occurrence of particular events. To correctly handle such situations a cloud infrastructure have to be reconfigured in a way that does not cause degradation in the overall performance. Otherwise, the quality of service specified in the service level agreement could be violated. To prevent such situations, the infrastructure could be organized as an autonomic system where self-adaptation and self-configuration techniques are implemented. Appropriate design choices become important in order not to fail in this goal. We propose a technique, based on a Petri net model and a specific analytical analysis approach, to represent Infrastructure-as-a-Service (IaaS) systems in the case in which the load conditions can suddenly change and reactive autonomic management techniques are applied to mitigate the consequences of the change. The model we propose is able to appropriately evaluate performance metrics in such critical situations making it suitable as a design tool for IaaS cloud systems. © 2015 IEEE.