Titlebook: Developing Networks using Artificial Intelligence; Haipeng Yao,Chunxiao Jiang,Yi Qian Book 2019 Springer Nature Switzerland AG 2019 machin

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Intelligence-Driven Networking Architecture,ware defined network facilitates 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, in this chapter, we propose NetworkAI, a new network architecture exploit

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音樂(lè)等

Intelligent Network Resource Management, placement in cloud computing. In this chapter, we propose a reinforcement learning based dynamic attribute matrix representation (RDAM) algorithm for virtual network embedding. The RDAM algorithm decomposes the process of node mapping into the following three steps: (1) static representation of sub

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Intention Based Networking Management,y eliminating manual configurations. It allows a user or administrator to send a simple request—using natural language—to plan, design and implement/operate the physical network which can improve network availability and agility. For example, an IT administrator can request improved voice quality fo

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2366-1186 ches to investigate solutions to intelligently monitor, control and optimize networking. The authors focus on four scenarios of successfully applying machine learning in network space. It also discusses the main challenge of network traffic intelligent awareness and introduces several machine learni

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