Deadline and Energy Aware Task Scheduling in Cloud Computing

Abstract

Cloud computing has recently emerged as a new paradigm for delivering on demand services over the internet. However, the expanding scale of data centers has made their energy consumption an imperative issue. Task scheduling is also an important issue in cloud computing which plays an important role to improve the overall performance and services of Cloud. However, the mapping of the cloud resources to process the user's requests is very challenging. Therefore, there is a pressing need for scheduling algorithms which take into consideration different parameters such as energy consumption, makespan, resources utilization and users priority. To address these issues, this paper proposes an efficient Deadline and Energy Aware Task Scheduling (DEATS) in Cloud Computing. The main goal of the proposed work is to increase the scheduling efficiency under deadline constraint and reduce the energy consumption of the cloud resources. DEATS algorithm gives full consideration to the dynamic characteristics of the cloud computing environment. Further, the proposed algorithm has been validated through 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 the resource utilization while meeting deadline constraints.