A Novel Heuristics based Energy Aware Resource Allocation and Job Prioritization in HPC Clouds

Cloud Computing provides the computational, storage, network and database resources to the consumers in a pay-as-per usage mode. In recent years, the data centers play a major role in hosting the cloud applications in the cloud infrastructure. The data centers are consuming huge electrical power and emits large amount of carbon footprint. It is essential to incorporate the Energy Efficient Resource Management (EERM) mechanism to control the electric power consumption and reduce the carbon footprint emission. EERA comprises of matching the user application requests with available cloud resources and allocating the user application requests to the matched cloud resources in an efficient manner. This paper mainly focused on proposing a novel heuristics based Energy Aware Resource Allocation (EARA) mechanism to allocate the user applications to the cloud resources that consumes minimal energy and incorporating the prioritization mechanism based on the deadline. It is simulated using the CloudSim toolkit and by generating High Performance Computing (HPC) type of application requests with the generated Eucalyptus based private Cloud environment. The results prove the effectiveness of the proposed mechanism in the cloud infrastructure by maximizing the number of users completed their applications within deadline and minimize the energy consumption in the