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A DQN-based CUBIC for TCP Congestion Control

In a static environment, as the available bandwidth increases, the slow congestion window increase rate prevents the existing TCP fully utilizing the bandwidth. CUBIC, a congestion control algorithm for high-speed networks, can provide higher throughput than existing algorithms but cannot guarantee satisfactory performance during frequent bandwidth fluctuations. Applying Deep-Q-Network to a TCP congestion control algorithm can improve link utilization. Therefore, in this paper, we propose a DQN-based CUBIC for various networks environments, which simultaneously utilizes the mechanisms of CUBIC and DQN. Through simulation experiments based on NS-3, it was confirmed that the proposed algorithm can increase the throughput compared to CUBIC in any link environment.