CLSDRL:A routing optimization method for traffic feature extraction

2021 International Conference on Networking and Network Applications (NaNA)(2021)

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摘要
In order to solve the impact of the temporal and spatial characteristics of traffic on network routing optimization, this paper proposes convolution long-short memory neural network deep reinforcement learning (CLSDRL) model for routing optimization. The CLSDRL model consists of deep deterministic policy gradients (DDPG) deep couple with convolution neural network (CNN) and long-short memory neura...
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关键词
deep reinforcement learning,routing optimization,neural network,deep leaning,software defined network
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