The invention discloses an SDN multistage
virtual network mapping method and device based on
reinforcement learning. The SDN multistage
virtual network mapping method comprises the steps: establishingand training a
reinforcement learning mapping model; for an underlying
virtual network request, obtaining current resource state information of a
physical network and inputting the current resource state information into the
reinforcement learning mapping model to perform underlying virtual node mapping; then, carrying out bottom layer
virtual link mapping solving; for an upper-layer virtual network request, obtaining current resource state information of a bottom-layer virtual network, inputting the current resource state information into the reinforcement learning mapping model, and performing upper-layer virtual node mapping; then, carrying out upper-layer
virtual link mapping solution; and if the mapping fails in any stage, dynamically adjusting the underlying virtual network until all nodes and links are successfully mapped. The SDN multistage
virtual network mapping device comprises a reinforcement learning module, a bottom-layer mapping module, an upper-layer mapping module anda dynamic adjustment module. The SDN multistage
virtual network mapping method and device are suitable for multistage
virtual network mapping, and can improve the overall request
acceptance rate.