Performance and Resource Prediction at High Utilization for N-Tier Service Systems in Cloud an Experiment Driven Approach

In cloud computing, one of its intensions is to meet service level agreements (SLAs) under high resource utilization. Cloud service providers normally make policies for the provisioning of resource sharing and performance optimization. As a result, the prediction of performance and resource utilization prior to the implementation deems as a promising and efficient tool for cloud providers. It is a challenge work due to the fact that requests of resource are always interacting and complex. Hence, the provisioning of an accurate model which capturing interactions between requests has become an impressing demand. Moreover, the dynamic feature of cloud environment brings more challenge to predict the performance of a running query or workload. To this end, this work develops an efficient and highly accurate resource sharing and performance evaluation model of n-tier service systems that take into account the interactions among concurrently running requests. The developed model extends experiment-driven approach is able to dynamically adapt changes and varieties in the workload and physical resource allocation. The developed model is trained and tested in light of Multi-tier application benchmark. The numerical results demonstrate that the developed models are accurate and effective.