  Message transmission and message synchronization for multicontroller
interdomain routing in software-defined networking (SDN) have long adaptation
times and slow convergence speeds, coupled with the shortcomings of traditional
interdomain routing methods, such as cumbersome configuration and inflexible
acquisition of network state information. These drawbacks make it difficult to
obtain a global state information of the network, and the optimal routing
decision cannot be made in real time, affecting network performance. This paper
proposes a cross-domain intelligent SDN routing method based on a proposed
multiagent deep reinforcement learning. First, the network is divided into
multiple subdomains managed by multiple local controllers, and the state
information of each subdomain is flexibly obtained by the designed SDN
multithreaded network measurement mechanism. Then, a cooperative communication
module is designed to realize message transmission and message synchronization
between root and local controllers, and socket technology is used to ensure the
reliability and stability of message transmission between multiple controllers
to realize the real-time acquisition of global network state information.
Finally, after the optimal intradomain and interdomain routing paths are
adaptively generated by the agents in the root and local controllers, a
prediction mechanism for the network traffic state is designed to improve the
awareness of the cross-domain intelligent routing method and enable the
generation of the optimal routing paths in the global network in real time.
Experimental results show that the proposed cross-domain intelligent routing
method can significantly improve the network throughput, reduce the network
delay and the packet loss rate compared to the Dijkstra and OSPF routing
methods.
