@inproceedings{2bd1f39dd56641f48b335d20be22ccda,
title = "Real-time Task Scheduling for joint energy efficiency optimization in data centers",
abstract = "The high energy consumption has become one bottleneck in the development of the data centers (DCs), where the main energy consumers are the cooling system and the servers. Therefore, the joint optimization for the energy efficiency of the cooling system and the servers is a crucial problem, while most of previous works on energy saving only studies one of these two components in an isolated manner. In this paper, we propose a real-time strategy, rTCS (real-time Task Classification and Scheduling strategy), to jointly optimize the energy efficiency of these two components in the scenario where the tasks arrive dynamically. Strategy rTCS first labels the tasks to classify them according to their run time and end time with a time complexity of O(1) and a bounded space complexity. Then, rTCS schedules the tasks in real time based on their labels and the energy consumption model of the DC. Simulation results show that rTCS can effectively improve the energy efficiency of DCs.",
keywords = "Cooling system, Data center, Energy efficiency, Real-time scheduling algorithm, Task classification",
author = "Youshi Wang and Fa Zhang and Rui Wang and Yangguang Shi and Hua Guo and Zhiyong Liu",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE Symposium on Computers and Communications, ISCC 2017 ; Conference date: 03-07-2017 Through 07-07-2017",
year = "2017",
month = sep,
day = "1",
doi = "10.1109/ISCC.2017.8024631",
language = "English",
series = "Proceedings - IEEE Symposium on Computers and Communications",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "838--843",
booktitle = "2017 IEEE Symposium on Computers and Communications, ISCC 2017",
address = "United States",
}
