Primary target of cloud provider is to provide the maximum resource utilization and increase the revenue by reducing energy consumption and operative cost. In the service providers point of view, resource allocation, resource sharing, migration of resources on demand, memory management, storage management, load balancing, energy efficient resource usage, computational complexity handling in virtualization are some of the major tasks that has to be dealt with. The major issue focused in this paper is to reduce the energy consumption problem and management of computation capacity utilization. For the same, an energy efficient resource management method is proposed to grip the resource scheduling and to minimize the energy utilized by the cloud datacenters for the computational work. Here a novel resource allocation mechanism is proposed, based on the optimization techniques. Also a novel dynamic virtual machine (VM) allocation method is suggested to help dynamic virtual machine allocation and job rescheduling to improve the consolidation of resources to execute the jobs. Experimental results indicated that proposed strategy outperforms as compared to the existing systems.
Fog Computing-Assisted Energy-Efficient Resource Allocation for High-Mobility MIMO-OFDMA Networks
