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.

中文翻译：

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软件定义数据中心中基于 DQN 的节能路由算法

随着智慧城市数据中心的快速发展，如何降低能耗、提高经济效益和网络性能正成为一个重要的研究课题。特别是，数据中心网络并不总是满负荷运行，这会导致大量的能源消耗。在本文中，我们重点关注基于软件定义网络的数据中心网络中的节能路由问题。针对软件定义数据中心带内控制模式的场景，我们制定了节能和控制器间负载均衡的双重优化目标。为了应对大的解决方案空间，我们设计了基于深度Q网络的节能路由算法来寻找流量的节能数据路径和交换机的控制路径。仿真结果表明，基于深度Q网络的节能路由算法只训练了部分状态，在控制平面上获得了良好的节能效果和负载均衡。与求解器和CERA启发式算法相比，基于深度Q网络的节能路由算法的节能效果与启发式算法几乎相同；但是，它的计算时间减少了很多，尤其是在大量流量场景下；设计和求解多目标优化问题更加灵活。基于深度Q网络的节能路由算法的节能效果与启发式算法几乎相同；但是，它的计算时间减少了很多，尤其是在大量流量场景下；设计和求解多目标优化问题更加灵活。基于深度Q网络的节能路由算法的节能效果与启发式算法几乎相同；但是，它的计算时间减少了很多，尤其是在大量流量场景下；设计和求解多目标优化问题更加灵活。