Doing Better Business: Trading a Little Execution Time for High Energy Saving under SLA Constraints
Dian Shen, Fang Dong, Junzhou Luo, Wei Wang, Xiang Fei, Guoqing Jin, Weidong Li · 2013
Large data centers are usually built to support the enormous computation and storage capability of Cloud Computing which has attracted people's attention nowadays. However, such large scale data centers generally consume an enormous amount of energy, which not only increases the running cost but also simultaneously enhances their greenhouse gas emissions. Addressing this issue, Virtualization technology is introduced, through which multiple Virtual Machines(VMs) can be centralized to fewer servers while allowing the idle servers to be dynamically powered off in order to save the energy consumption. In the paper, we investigate the impact of Virtualization technology on the energy and performance in data center environment taking into consideration various factors such as server failures and the overhead introduced by the VM contention. Noticing that there exits a tradeoff between energy consumption and execution time, we propose a stochastic model of data centers using Queueing theory to optimize performance and energy consumption. From the data center operators' prospective, they are willing to do better business by saving the energy consumption while abiding by the SLAs. Therefore, we try to find an optimal Energy-Performance tradeoff policy for the data center operators to operate data centers. The simulation results show that our model can significantly reduce the energy consumption by up to 35.4 while sacrificing a little execution time.