CCLab is an adversarial testing framework showing learning-based congestion controllers are generally more robust than traditional human-designed ones under feature- and environment-level attacks, with adversarial traces usable to train improved controllers.
Toward fair and efficient congestion control: Machine learning aided congestion control (mlacc)
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CCLab: Adversarial Testing of Learning- and Non-Learning-Based Congestion Controllers
CCLab is an adversarial testing framework showing learning-based congestion controllers are generally more robust than traditional human-designed ones under feature- and environment-level attacks, with adversarial traces usable to train improved controllers.