Dynamic Resource Allocation Using Fuzzy Prediction System

Virtualization is the main technology in the large scale data centers with which resources are shared among different application running on different VMs. Virtualization through virtual machine monitor (VMM) like Yen only provides resource isolation among co-located VMs. However, it has been shown that resource isolation does not imply performance isolation between VMs. Hence it necessitates on-demand allocation of the physical shared resources to individual VM as per their dynamic requirements to satisfy the SLA between customer and cloud provider. To do this efficiently future resource utilization is predicted using fuzzy logic based prediction. To avoid underestimation prediction errors due to spikes in the workload, the predicted values are padded with proper value and immediately resource caps are raised. The resource conflict is resolved locally if resources are available otherwise migration is triggered. This scheme allocates resources efficiently and reduces the response time as compared to static allocation. The resource saving with proposed method is around 30-40% and around 10-20% performance improvement in terms of response time of an application.