DDPG-Based Energy-Efficient Flow Scheduling Algorithm in Software-Defined Data Centers
With the rapid development of data centers, the energy consumption brought by more and more data centers cannot be underestimated. How to intelligently manage software-defined data center networks to reduce network energy consumption and improve network performance is becoming an important research...
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| Published in | Wireless communications and mobile computing Vol. 2021; no. 1 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Oxford
Hindawi
2021
John Wiley & Sons, Inc |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1530-8669 1530-8677 1530-8677 |
| DOI | 10.1155/2021/6629852 |
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| Abstract | With the rapid development of data centers, the energy consumption brought by more and more data centers cannot be underestimated. How to intelligently manage software-defined data center networks to reduce network energy consumption and improve network performance is becoming an important research subject. In this paper, for the flows with deadline requirements, we study how to design the rate-variable flow scheduling scheme to realize energy-saving and minimize the mean completion time (MCT) of flows based on meeting the deadline requirement. The flow scheduling optimization problem can be modeled as a Markov decision process (MDP). To cope with a large solution space, we design a DDPG-EEFS algorithm to find the optimal scheduling scheme for flows. The simulation result reveals that the DDPG-EEFS algorithm only trains part of the states and gets a good energy-saving effect and network performance. When the traffic intensity is small, the transmission time performance can be improved by sacrificing a little energy efficiency. |
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| AbstractList | With the rapid development of data centers, the energy consumption brought by more and more data centers cannot be underestimated. How to intelligently manage software-defined data center networks to reduce network energy consumption and improve network performance is becoming an important research subject. In this paper, for the flows with deadline requirements, we study how to design the rate-variable flow scheduling scheme to realize energy-saving and minimize the mean completion time (MCT) of flows based on meeting the deadline requirement. The flow scheduling optimization problem can be modeled as a Markov decision process (MDP). To cope with a large solution space, we design a DDPG-EEFS algorithm to find the optimal scheduling scheme for flows. The simulation result reveals that the DDPG-EEFS algorithm only trains part of the states and gets a good energy-saving effect and network performance. When the traffic intensity is small, the transmission time performance can be improved by sacrificing a little energy efficiency. |
| Author | Qiu, Xuesong Wang, Ying Yu, Peng Yao, Zan Meng, Luoming |
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| Copyright | Copyright © 2021 Zan Yao et al. Copyright © 2021 Zan Yao et al. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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| SubjectTerms | Algorithms Completion time Computer centers Connectivity Control algorithms Data centers Design Energy consumption Energy efficiency Heuristic Linear programming Markov analysis Markov processes Optimization Quality of service Scheduling Software Solution space Traffic control |
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| Title | DDPG-Based Energy-Efficient Flow Scheduling Algorithm in Software-Defined Data Centers |
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