Jan 4, 2021 · In this paper, we have developed the efficient IoT traffic monitoring solution employing the advances of SDN and deep reinforcement learning ...

In this paper, we propose an IoT traffic monitoring approach that implements deep reinforcement learning technique to maximize the fine-grained monitoring ...

Sep 23, 2024 · This paper proposes a novel traffic monitoring framework, namely, DeepMonitor, for SDN-based IoT networks to provide fine-grained traffic ...

In this paper, we propose an IoT traffic monitoring approach that implements deep reinforcement learning technique to maximize the fine-grained monitoring ...

We then formulate our control optimization problem by employing the Markov decision process (MDP). Afterwards, we develop Double Deep Q-Network (DDQN) algorithm ...

Efficient SDN-Based Traffic Monitoring in IoT Networks with Double Deep Q-Network. T. Nguyen, T. Phan, D. Hoang, T. Nguyen, and C. So-In.

Efficient SDN-Based Traffic Monitoring in IoT Networks with Double Deep Q-Network. https://doi.org/10.1007/978-3-030-66046-8_3 ·. Journal: Computational Data ...

Efficient SDN-Based Traffic Monitoring in IoT Networks with Double Deep Q-Network ... reinforcement learning for traffic monitoring in SDN-based IoT networks.

Get details about the chapter of Efficient SDN-Based Traffic Monitoring in IoT Networks with Double Deep Q-Network from book Computational Data and Social ...

Aug 9, 2021 · This paper proposes a novel traffic monitoring framework, namely, DeepMonitor, for SDN-based IoT networks to provide fine-grained traffic analysis capability.