Energy-efficient task scheduling algorithm in the heterogeneous cloud data centerEnergy-efficient task scheduling algorithm in the heterogeneous cloud data center

Cloud service usage has been significantly increased due to ease of access, improved performance, and low costs. Task scheduling is one of the most important areas of research in cloud computing. Task scheduling refers to how tasks are assigned to resources in a way that improves system performance. Using an efficient scheduler can improve energy consumption and resource utilization. Users want to get tasks done faster, while cloud provider aims to reduce energy consumption and increase profits. However, there is a conflict between minimizing makespan and minimizing energy consumption. This paper presents an Energy-efficient Task Scheduling (ETS) algorithm in a cloud environment that simultaneously considers the conflicting parameters of energy consumption, makespan, and load. The performance of the proposed algorithm is evaluated using the CloudSim simulator. Experimental results show that the proposed algorithm performs better in terms of makespan, efficiency, success rate, degree of imbalance, and processor utilization compared to the HPSO, BBMO, ERR, and FUGE algorithms.

Keywords:

Cloud , Task scheduling , Energy consumption , Makespan.