An Energy-Efficient Hybrid Scheduling Algorithm for Task Scheduling in the Cloud Computing Environments

The main intent of the cloud computing to provide utilities demands users that are booming day by day. To meet requirements, existing scheduling algorithms focus on improving performance and neglecting energy consumed fulfill those demands. Hence, we propose a new Hybrid Scheduling Algorithm (HS) which is based Genetic (GA) Flower Pollination (FPA) for environments. proposed algorithm has surpassed in terms across various parameters, i.e. completion time, resource utilization, cost computation, consumption both environments than (GA FPA). simulation results revealed HS demonstrated maximum utilization with minimum less time execution tasks as compared have shown resources, 36% better GA 16% FPA homogeneous environment whereas heterogenous environment, performed 12% 3.8% FPA. an improvement 2.6% from 6.9% reduced 17.8% 33.7% heterogeneous environment. For consumption, improved 22% 11% 4% 14%