An Efficient Energy-Aware Tasks Scheduling with Deadline-Constrained in Cloud Computing

Nowadays, Cloud Computing (CC) has emerged as a new paradigm for hosting and delivering services over the Internet. However, the wider deployment of Cloud and the rapid increase in the capacity, as well as the size of data centers, induces a tremendous rise in electricity consumption, escalating data center ownership costs and increasing carbon footprints. This expanding scale of data centers has made energy consumption an imperative issue. Besides, users' requirements regarding execution time, deadline, QoS have become more sophisticated and demanding. These requirements often conflict with the objectives of cloud providers, especially in a high-stress environment in which the tasks have very critical deadlines. To address these issues, this paper proposes an efficient Energy-Aware Tasks Scheduling with Deadline-constrained in Cloud Computing (EATSD). The main goal of the proposed solution is to reduce the energy consumption of the cloud resources, consider different users' priorities and optimize the makespan under the deadlines constraints. Further, the proposed algorithm has been simulated using the CloudSim simulator. The experimental results validate that the proposed approach can effectively achieve good performance by minimizing the makespan, reducing energy consumption and improving resource utilization while meeting deadline constraints.