A Near-Optimal Control Policy in Cloud Systems with Renewable Sources and Time-Dependent Energy Price
- Authors
- Liu, Jiashang; Lee, Joohyun; Shroff, Ness B.; Sinha, Prasun; Wang, Sinong
- Issue Date
- Jul-2018
- Publisher
- IEEE Computer Society
- Keywords
- Electricity bill minimization; Lyapunov optimization; Markov decision process; Renewable energy; Server on off control; Turn on cost
- Citation
- IEEE International Conference on Cloud Computing, CLOUD, v.2018-July, pp.702 - 709
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE International Conference on Cloud Computing, CLOUD
- Volume
- 2018-July
- Start Page
- 702
- End Page
- 709
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/7893
- DOI
- 10.1109/CLOUD.2018.00096
- ISSN
- 2159-6182
- Abstract
- The cost of energy usage is of significant concern in cloud/data center systems that support a large number of servers. A simple way to reduce energy consumption and the electricity bill is to turn some of the servers off during periods of under utilization. However, turning a server back on typically consumes a lot of energy. Another way to reduce the energy cost is to equip cloud systems with renewable resources and batteries. Most works in the literature have focused on one or the other approach. In this work, we propose a joint server on-off and energy control policy, which determines the servers' on-off status, as well as the energy purchasing behavior, by taking electricity price, renewable resources, possible future tasks and turn-on cost into account. The server on-off control component is proved to be optimal in terms of energy consumption minimization. The joint policy is shown to be arbitrarily close to the optimal solution in terms of electricity bill minimization, in the case where the battery has infinite capacity with stable energy level. Simulation results show that even under reasonable battery size, a significant electricity cost reduction is achieved with the proposed policy. © 2018 IEEE.
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