TY - JOUR
T1 - Energy cost minimization with job security guarantee in Internet data center
AU - Li, Zhongjin
AU - Ge, Jidong
AU - Li, Chuanyi
AU - Yang, Hongji
AU - Hu, Haiyang
AU - Luo, Bin
AU - Chang, Victor
N1 - Funding Information:
This work was supported by the Key Program of Research and Development of China (2016YFC0800803), the National Natural Science Foundation, China (No. 61272188, 61572162, 61572251), the Natural Science Foundation of Jiangsu Province (No. BK20131277), the Open Foundation of State key Laboratory of Networking and Switching Technology (Beijing University of Posts and Telecommunications) (SKLNST-2013-1-14), the Fundamental Research Funds for the Central Universities.
Publisher Copyright:
© 2016 Elsevier B.V.
PY - 2017/8/1
Y1 - 2017/8/1
N2 - With the proliferation of various big data applications and resource demand from Internet data centers (IDCs), the energy cost has been skyrocketing, and it attracts a great deal of attention and brings many energy optimization management issues. However, the security problem for a wide range of applications, which has been overlooked, is another critical concern and even ranked as the greatest challenge in IDC. In this paper, we propose an energy cost minimization (ECM) algorithm with job security guarantee for IDC in deregulated electricity markets. Randomly arriving jobs are routed to a FIFO queue, and a heuristic algorithm is devised to select security levels for guaranteeing job risk probability constraint. Then, the energy optimization problem is formulated by taking the temporal diversity of electricity price into account. Finally, an online energy cost minimization algorithm is designed to solve the problem by Lyapunov optimization framework which offers provable energy cost optimization and delay guarantee. This algorithm can aggressively and adaptively seize the timing of low electricity price to process workloads and defer delay-tolerant workloads execution when the price is high. Based on the real-life electricity price, simulation results prove the feasibility and effectiveness of proposed algorithm.
AB - With the proliferation of various big data applications and resource demand from Internet data centers (IDCs), the energy cost has been skyrocketing, and it attracts a great deal of attention and brings many energy optimization management issues. However, the security problem for a wide range of applications, which has been overlooked, is another critical concern and even ranked as the greatest challenge in IDC. In this paper, we propose an energy cost minimization (ECM) algorithm with job security guarantee for IDC in deregulated electricity markets. Randomly arriving jobs are routed to a FIFO queue, and a heuristic algorithm is devised to select security levels for guaranteeing job risk probability constraint. Then, the energy optimization problem is formulated by taking the temporal diversity of electricity price into account. Finally, an online energy cost minimization algorithm is designed to solve the problem by Lyapunov optimization framework which offers provable energy cost optimization and delay guarantee. This algorithm can aggressively and adaptively seize the timing of low electricity price to process workloads and defer delay-tolerant workloads execution when the price is high. Based on the real-life electricity price, simulation results prove the feasibility and effectiveness of proposed algorithm.
KW - Deregulated electricity markets
KW - Energy cost minimization
KW - Internet data center
KW - Risk probability constraint
KW - Security service
UR - http://www.scopus.com/inward/record.url?scp=85009265581&partnerID=8YFLogxK
U2 - 10.1016/j.future.2016.12.017
DO - 10.1016/j.future.2016.12.017
M3 - Article
AN - SCOPUS:85009265581
SN - 0167-739X
VL - 73
SP - 63
EP - 78
JO - Future Generation Computer Systems
JF - Future Generation Computer Systems
ER -