DQN-based energy-efficient routing algorithm in software-defined data centers
With the rapid development of data centers in smart cities, how to reduce energy consumption and how to raise economic benefits and network performance are becoming an important research subject. In particular, data center networks do not always run at full load, which leads to significant energy co...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-06-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147720935775 |
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| _version_ | 1832547261585817600 |
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| author | Zan Yao Ying Wang Xuesong Qiu |
| author_facet | Zan Yao Ying Wang Xuesong Qiu |
| author_sort | Zan Yao |
| collection | DOAJ |
| description | With the rapid development of data centers in smart cities, how to reduce energy consumption and how to raise economic benefits and network performance are becoming an important research subject. In particular, data center networks do not always run at full load, which leads to significant energy consumption. In this article, we focus on the energy-efficient routing problem in software-defined network–based data center networks. For the scenario of in-band control mode of software-defined data centers, we formulate the dual optimal objective of energy-saving and the load balancing between controllers. In order to cope with a large solution space, we design the deep Q-network-based energy-efficient routing algorithm to find the energy-efficient data paths for traffic flow and control paths for switches. The simulation result reveals that the deep Q-network-based energy-efficient routing algorithm only trains part of the states and gets a good energy-saving effect and load balancing in control plane. Compared with the solver and the CERA heuristic algorithm, energy-saving effect of the deep Q-network-based energy-efficient routing algorithm is almost the same as the heuristic algorithm; however, its calculation time is reduced a lot, especially in a large number of flow scenarios; and it is more flexible to design and resolve the multi-objective optimization problem. |
| format | Article |
| id | doaj-art-f683561d5df74156bcd04fcc7d805b11 |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2020-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-f683561d5df74156bcd04fcc7d805b112025-02-03T06:45:29ZengWileyInternational Journal of Distributed Sensor Networks1550-14772020-06-011610.1177/1550147720935775DQN-based energy-efficient routing algorithm in software-defined data centersZan YaoYing WangXuesong QiuWith the rapid development of data centers in smart cities, how to reduce energy consumption and how to raise economic benefits and network performance are becoming an important research subject. In particular, data center networks do not always run at full load, which leads to significant energy consumption. In this article, we focus on the energy-efficient routing problem in software-defined network–based data center networks. For the scenario of in-band control mode of software-defined data centers, we formulate the dual optimal objective of energy-saving and the load balancing between controllers. In order to cope with a large solution space, we design the deep Q-network-based energy-efficient routing algorithm to find the energy-efficient data paths for traffic flow and control paths for switches. The simulation result reveals that the deep Q-network-based energy-efficient routing algorithm only trains part of the states and gets a good energy-saving effect and load balancing in control plane. Compared with the solver and the CERA heuristic algorithm, energy-saving effect of the deep Q-network-based energy-efficient routing algorithm is almost the same as the heuristic algorithm; however, its calculation time is reduced a lot, especially in a large number of flow scenarios; and it is more flexible to design and resolve the multi-objective optimization problem.https://doi.org/10.1177/1550147720935775 |
| spellingShingle | Zan Yao Ying Wang Xuesong Qiu DQN-based energy-efficient routing algorithm in software-defined data centers International Journal of Distributed Sensor Networks |
| title | DQN-based energy-efficient routing algorithm in software-defined data centers |
| title_full | DQN-based energy-efficient routing algorithm in software-defined data centers |
| title_fullStr | DQN-based energy-efficient routing algorithm in software-defined data centers |
| title_full_unstemmed | DQN-based energy-efficient routing algorithm in software-defined data centers |
| title_short | DQN-based energy-efficient routing algorithm in software-defined data centers |
| title_sort | dqn based energy efficient routing algorithm in software defined data centers |
| url | https://doi.org/10.1177/1550147720935775 |
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