Autonomic Cloud Resource Management

Resource utilization of cloud affect the operational cost of cloud services. Since cloud user and demands increasing exponentially, the service provider needs to manage the recourse accordingly so that maximum profit can be provide to the service provider as well as cloud user with the quality of service constraint (QoS). To maintain QoS, service level agreement (SLA) violation rate, energy consumption by resources, cost, and execution time should be less. The energy efficiency and SLA violation rate are the major focused key point of this work. In this paper, energy consumption has been reducing through self-optimization, and SLA violation rate is minimized by self-healing methods and separate faulty VM from the resource pool. In continue, the operating cost of resources has been optimizing and less execution time has recorded. The proposed method is simulated in cloudsim toolkit, evaluates the performance metrics with a different set of workloads and the observation of this research and its experimental results and comparative analysis with existing frameworks are evidence of utmost performance.