A Fuzzy Approach to Cloud Admission Control for Safe Overbooking

Cloud computing enables elasticity rapid provisioning and deprovisioning of computational resources. Elasticity allows cloud users to quickly adapt resource allocation to meet changes in their workloads. For cloud providers, elasticity complicates capacity management as the amount of resources that can be requested by users is unknown and can vary significantly over time. Overbooking techniques allow providers to increase utilization of their data centers. For safe overbooking, cloud providers need admission control mechanisms to handle the tradeoff between increased utilization (and revenue), and risk of exhausting resources, potentially resulting in penalty fees and/or lost customers. We propose a flexible approach (implemented with fuzzy logic programming) to admission control and the associated risk estimation. Our measures exploit different fuzzy logic operators in order to model optimistic, realistic, and pessimistic behaviour under uncertainty. The application has been coded with the MALP language by using the FLOPER system developed in our research group. An experimental evaluation confirm that our fuzzy admission control approach can significantly increase resource utilization while minimizing the risk of exceeding the total available capacity.