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Title: NetworkAI: An Intelligent Network Architecture for Self-Learning Control Strategies in Software Defined Networks
Authors: Yao, H
Mai, T
Xu, X
Zhang, P
Li, M
Liu, Y
Keywords: NetworkAI;Software Defined Networks;In-band Network Telemetry;Deep Reinforcement Learning
Issue Date: 24-Jul-2018
Publisher: IEEE
Citation: IEEE Internet of Things Journal, 2018
Abstract: The past few years have witnessed a wide deployment of software defined networks facilitating a separation of the control plane from the forwarding plane. However, the work on the control plane largely relies on a manual process in configuring forwarding strategies. To address this issue, this paper presents NetworkAI, an intelligent architecture for self-learning control strategies in SDN networks. NetworkAI employs deep reinforcement learning and incorporates network monitoring technologies such as the in-band network telemetry to dynamically generate control policies and produces a near optimal decision. Simulation results demonstrated the effectiveness of NetworkAI.
Appears in Collections:Dept of Electronic and Computer Engineering Research Papers

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