Vienna University of Economics and Business
Cloud providers aim at guaranteeing Service Level Agreements (SLAs) in a resource-efficient way. This, amongst others, means that resources of Virtual (VMs) and Physical Machines (PMs) have to be autonomically allocated responding to external influences as workload or environmental changes. Thereby, Workload Volatility (WV) is one of the crucial factors that influence the quality of suggested allocations. In this paper, the authors devise a novel approach for self-adaptive and resource efficient decision-making considering the three conflicting goals of minimizing the number of SLA violations, maximizing resource utilization, and minimizing the number of necessary time- and energy-consuming reconfiguration actions.