ANN-Based Resource Scheduling Mechanism in Hybrid Cloud Computing Environment

Cloud computing is an emerging web-based field where most of the researchers are contributing their best. Cloud computing has gained its popularity because of its distinguishing characteristics, i.e., on-demand resource availability, centralized data storage, pay per use model and many more. Out of various associated challenges, one major challenge that is faced by the researchers in this field is precise and rational scheduling of resources between various cloudlets in hybrid cloud-based models. During the hybridization of deployment models, there is need of resource scheduling whereby resources are allocated while keeping watch on response time and CPU utilization when implementing on cloud-based infrastructure. Our proposed approach uses an artificial intelligence-based model to provide scheduling sequence to various jobs in cloud computing environments as artificial intelligence has benefitted cloud computing in number of ways. The proposed model will provide scheduling sequence, i.e., the order in which cloud-based jobs will be allocated to the particular cloud for requested resources. Results that we have got after using the proposed approach are promising in terms of improved response time, increased accuracy level and improved CPU utilization. In addition to the mentioned improvements, the proposed model is also providing better scalability while maintaining cost-effectiveness. As a whole, the results obtained are inspiring.