TY - GEN
T1 - Optimal power and workload management for green data centers with thermal storage
AU - Guo, Yuanxiong
AU - Gong, Yanmin
AU - Fang, Yuguang
AU - Khargonekar, Pramod P.
AU - Geng, Xiaojun
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2013
Y1 - 2013
N2 - Reducing the carbon footprint of data centers is becoming a primary goal of large IT companies. Due to the intermittency and unpredictability of renewable energy sources such as wind and solar, it is quite challenging to utilize them in data centers. In this paper, we explore the opportunities offered by delay-tolerant workloads and thermal storage to facilitate the renewable energy integration in data centers and meanwhile, reduce the cost of using brown energy (i.e., energy from the utility grid). A stochastic optimization problem is formulated to tackle the stochastic renewable generation and workload arrival processes. Then, an online control algorithm based on the Lyapunov optimization approach is proposed to solve it. Simulation results based on the real-world traces show the effectiveness of the algorithm in practice. © 2013 IEEE.
AB - Reducing the carbon footprint of data centers is becoming a primary goal of large IT companies. Due to the intermittency and unpredictability of renewable energy sources such as wind and solar, it is quite challenging to utilize them in data centers. In this paper, we explore the opportunities offered by delay-tolerant workloads and thermal storage to facilitate the renewable energy integration in data centers and meanwhile, reduce the cost of using brown energy (i.e., energy from the utility grid). A stochastic optimization problem is formulated to tackle the stochastic renewable generation and workload arrival processes. Then, an online control algorithm based on the Lyapunov optimization approach is proposed to solve it. Simulation results based on the real-world traces show the effectiveness of the algorithm in practice. © 2013 IEEE.
KW - batch workloads
KW - data center
KW - Lyapunov optimization
KW - Renewable energy
KW - thermal storage
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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84904125587&origin=recordpage
U2 - 10.1109/GLOCOM.2013.6831509
DO - 10.1109/GLOCOM.2013.6831509
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781479913534
T3 - GLOBECOM - IEEE Global Telecommunications Conference
SP - 2866
EP - 2871
BT - 2013 IEEE Global Communications Conference, GLOBECOM 2013
PB - IEEE
T2 - 2013 IEEE Global Communications Conference, GLOBECOM 2013
Y2 - 9 December 2013 through 13 December 2013
ER -
