Energy-Efficient task scheduling in cloud data center- A temperature aware approach

Most of the previous studies based on task scheduling deals with either optimizing computing energy or performance upgradation only. However with advancement of cloud data center the users requirements are being diversified that is not achieved through traditional scheduling algorithm. One of the demand is to minimize cost related to cooling the data center. From the literature survey we found that the cooling energy cost half millions dollar to computing energy cost. In order to provide cost-effective executions in cloud environment, appropriate task scheduling strategy is necessary. Temperature affects not only the reliability but also the performance, power and cost of the embedded system. This paper proposes a thermalaware task allocation and scheduling algorithm for cloud data center. The task scheduling is designed in such a way that not only minimizes computation cost, it also reduces cooling. The rigorous simulation has been performed and compared with state of the art algorithms. The experimental results show that the thermalaware task scheduling algorithm outperforms compared to other strategies.