EAN: 9789811948732

SPRINGERBRIEFS IN COMPUTER SCIENCE BRINGING M...

Emerging machine learning techniques bring new opportunities to flexible network control and
management. This book focuses on using state-of-the-art machine learning-based approaches to
improve the performance of Software-Defined Networking (SDN). It will apply several innovative
machine learning methods (e.g.  Deep Reinforcement Learning  Multi-Agent Reinforcement Learning
and Graph Neural Network) to traffic engineering and controller load balancing in
software-defined wide area networks  as well as flow scheduling  coflow scheduling  and flow
migration for network function virtualization in software-defined data center networks. It
helps readers reflect on several practical problems of deploying SDN and learn how to solve the
problems by taking advantage of existing machine learning techniques. The book elaborates on
the formulation of each problem  explains design details for each scheme  and provides
solutions by running mathematical optimization processes  conducting simulated experiments  and
analyzing the experimental results.

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