A multi objective optimization for different services in green cloud environment

Background: an energy efficient multi objective optimization technique is planned for a multiple cloud service rendering by heterogeneous user tasks. This optimization technique is employed to efficiently optimize the energy resources and enhance the reliability with minimum operation cost. Materials and Methods: Multi Objective Optimal Energy for Service Rendering (MOOE-SR) technique is developed to attain an energy efficient green cloud service provisioning. In MOOE-SR, Multi Objective particle swarm optimization approach is used to analyze the status of multiple services with its energy requirement and power saving ability in the green cloud environment of heterogeneous user tasks. Results: The proposed Multi Objective Optimal Energy for Service Rendering (MOOE-SR) technique is implemented by using java language with CloudSim simulator environment. An experimental result shows the performance of proposed work in terms of energy consumption, execution time, operation cost and utility rate. Conclusion: The Multi Objective particle swarm optimization technique is achieved for efficiently optimize the energy resources and improves the reliability with minimum operation cost. Main Conclusions: finally, MOOE-SR technique is introduced to minimizing the energy consumption, improving the utility rate, minimum operation cost and also minimum time taken to complete the user task for service provisioning in green cloud environment.