Real-Time Task Scheduling for Joint Energy Efficiency Optimization in Data Centers

被引：0

作者：

Wang, Youshi ^{[1
,2
]}

Zhang, Fa ^{[3
]}

Wang, Rui ^{[4
]}

Shi, Yangguang ^{[5
]}

Guo, Hua ^{[6
]}

Liu, Zhiyong ^{[2
,7
]}

机构：

[1] Univ Chinese Acad Sci, Beijing, Peoples R China

[2] Chinese Acad Sci, ICT, Beijing Key Lab Mobile Comp & Pervas Device, Beijing, Peoples R China

[3] Chinese Acad Sci, ICT, Key Lab Intelligent Informat Proc, Beijing, Peoples R China

[4] Hong Kong Univ Sci & Technol, Hong Kong, Hong Kong, Peoples R China

[5] Technion Israel Inst Technol, Haifa, Israel

[6] State Grid Jingzhou Elect Power Co, Jingzhou, Hubei, Peoples R China

[7] Chinese Acad Sci, ICT, State Key Lab Comp Architecture, Beijing, Peoples R China

来源：

2017 IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATIONS (ISCC) | 2017年

基金：

中国国家自然科学基金;

关键词：

energy efficiency; data center; cooling system; task classification; real-time scheduling algorithm;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：838 / 843

页数：6

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