Joint Workload Scheduling and Energy Management for Green Data Centers Powered by Fuel Cells

被引：22

作者：

Hu, Xiaoxuan ^{[1
]}

Li, Peng ^{[2
]}

Wang, Kun ^{[3
]}

Sun, Yanfei ^{[1
]}

Zeng, Deze ^{[4
]}

Wang, Xiaoyan ^{[5
]}

Guo, Song ^{[3
]}

机构：

[1] Nanjing Univ Posts & Telecommun, Sch Automat, Nanjing 210003, Peoples R China

[2] Univ Aizu, Sch Comp Sci & Engn, Aizu Wakamatsu, Fukushima 9658580, Japan

[3] Hong Kong Polytech Univ, Dept Comp, Hong Kong, Peoples R China

[4] China Univ Geosci, Dept Comp Sci, Wuhan 430074, Peoples R China

[5] Ibaraki Univ, Grad Sch Sci & Engn, Hitachi, Ibaraki 3168511, Japan

来源：

IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING | 2019年 / 3卷 / 02期

关键词：

Fuel cell; data center; Lyapunov optimization; cost minimization; job scheduling;

D O I：

10.1109/TGCN.2019.2893712

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

The fuel cell is a promising power source for green data centers due to its high energy efficiency, low carbon emissions, and high reliability. However, because of the mechanical limitations related to fuel delivery, fuel cells are slow in adjusting power output when the energy demand quickly changes, which is called limited load following. Many recent work have studied to mitigate the limited load following by using energy storage to adjust energy supply, but achieves limited successes because of the constraint of energy storage size. In this paper, we address this challenge by changing both energy supply and demand, via joint workload scheduling and energy management. Specifically, we consider multiple geo-distributed data centers powered by both fuel cells and energy storage. An online algorithm has been proposed to minimize the gap between energy supply and demand by jointly managing the fuel cells output and migrating workloads among data centers. Simulations results based on real-world traces show that the proposed algorithms can achieve satisfactory performance.

引用

页码：397 / 406

页数：10

共 23 条

[1] Fuel Cell Power Management Using Genetic Expression Programming in All-Electric Ships [J].

Abkenar, Alireza Tashakori ;

Nazari, Ali ;

Jayasinghe, Shantha D. Gamini ;

Kapoor, Ajay ;

Negnevitsky, Michael .

IEEE TRANSACTIONS ON ENERGY CONVERSION, 2017, 32 (02) :779-787

[2]

[Anonymous], 2011, P ACM SIGMETRICS JOI

[3] Probabilistic Model Checking and Scheduling Implementation of an Energy Router System in Energy Internet for Green Cities [J].

Gao, Min ;

Wang, Kun ;

He, Lei .

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2018, 14 (04) :1501-1510

[4] Energy and Network Aware Workload Management for Sustainable Data Centers with Thermal Storage [J].

Guo, Yuanxiong ;

Gong, Yanmin ;

Fang, Yuguang ;

Khargonekar, Pramod P. ;

Geng, Xiaojun .

IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2014, 25 (08) :2030-2042

[5] Building Fuel Powered Supercomputing Data Center at Low Cost [J].

Hua, Yiqing ;

Li, Chao ;

Tang, Weichao ;

Jiang, Li ;

Liang, Xiaoyao .

PROCEEDINGS OF THE 29TH ACM INTERNATIONAL CONFERENCE ON SUPERCOMPUTING (ICS'15), 2015, :241-250

[6] Fuel Cell Power Systems and Applications [J].

Lai, Jih-Sheng ;

Ellis, Michael W. .

PROCEEDINGS OF THE IEEE, 2017, 105 (11) :2166-2190

[7] CBRM: Computational Reputation Model for C2C e-Commerce Platform [J].

Li, Xueqin ;

Li, Cong ;

Ma, Li .

2014 SEVENTH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN (ISCID 2014), VOL 2, 2014,

[8]

Li Y, 2016, INT S HIGH PERF COMP, P444, DOI 10.1109/HPCA.2016.7446085

[9]

Lin MH, 2012, 2012 INTERNATIONAL GREEN COMPUTING CONFERENCE (IGCC)

[10]

Neely Michael J., 2010, Stochastic Network Optimization With Application to Communication and Queueing Systems, DOI [10.2200/S00271ED1V01Y201006CNT007, DOI 10.2200/S00271ED1V01Y201006CNT007]

← 1 2 3 →