A Novel Approach to Minimize the Energy Consumption Using Task Scheduling in Cloud Data Centers

Data centers play an important role in the modern computational virtual environment. The data center is made up of servers, storage devices, cooling equipment’s, and power delivery equipment’s to deliver general services such as platform-as-a-service (PaaS), software-as-a-service (SaaS), and infrastructure-as-a-service (IaaS). In this aspect, all the devices are generating more heat since all are electronics devices. It increases the power consumption and carbon emission in the environment also. As a result, it may lead to be a part of possibility of global warming. So, the carbon emission should be minimized in the entry level. In this paper, it is achieved this with the help of task scheduling. To minimize the same and improve the efficiency, we have tested three task scheduling algorithms: TPPC, RASA, and PALB. The experimentation results of all are these algorithms are compared, and then the differences in terms of efficiency and carbon minimization are also analyzed. The results are given in the comparative analysis.