No abstract

Cloud Computing is an eminent and reputable agenda which relies on large-scale distributed processing to provide access to their resources and services. In the cloud environment a rigorous management system is mandatory to collect all information regarding task processing levels and proving impartial resource provisioning through the levels of Quality of Service (QoS). These concerns can be settled by employing a meta-heuristic optimization-based resource management. Subsequently, this paper presents a Fuzzy Emperor Penguin Optimization (Fuzzy-EPO) algorithm-based resource provisioning framework for heterogeneous cloud environment. To deploy the optimal set of virtual machines (VM) to physical machines the VM allocation model is employed. The proposed Fuzzy-EPO algorithm does the VM consolidation mainly to reallocate overloaded VM to under-loaded PM to minimize the migration time and the brownout mechanism is adopted to reduce the rate of energy consumption. CloudSim simulation platform is used to implement the proposed system. The simulation results expose that the proposed Fuzzy -EPO based system is effective in restraining the proportion of SLA violation and increasing QoS requirements for providing proficient cloud service