It takes the average reader 1 hour and 20 minutes to read Bringing Machine Learning to Software-Defined Networks by Zehua Guo
Assuming a reading speed of 250 words per minute. Learn more
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.
Bringing Machine Learning to Software-Defined Networks by Zehua Guo is 78 pages long, and a total of 20,124 words.
This makes it 26% the length of the average book. It also has 25% more words than the average book.
The average oral reading speed is 183 words per minute. This means it takes 1 hour and 49 minutes to read Bringing Machine Learning to Software-Defined Networks aloud.
Bringing Machine Learning to Software-Defined Networks is suitable for students ages 10 and up.
Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.
When deciding what to show young students always use your best judgement and consult a professional.
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