9789811948732 - bringing machine learning to software-defined networks di guo, zehua (18 risultati)
Lingua: Inglese
Editore: Springer Verlag, Singapore, Singapore 2022
Serie: SpringerBriefs in Computer Science, Libro 15 di 83. Libro 15 di 83 - SpringerBriefs in Computer Science
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Paperback. Condizione: new. Paperback. 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 le…arning 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Lingua: Inglese
Editore: Springer 2022
Serie: SpringerBriefs in Computer Science, Libro 15 di 83. Libro 15 di 83 - SpringerBriefs in Computer Science
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Editore: Springer 2022
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Editore: Springer 2022
Serie: SpringerBriefs in Computer Science, Libro 15 di 83. Libro 15 di 83 - SpringerBriefs in Computer Science
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Condizione: New. 1st ed. 2022 edition NO-PA16APR2015-KAP.
Lingua: Inglese
Editore: Springer 2022
Serie: SpringerBriefs in Computer Science, Libro 15 di 83. Libro 15 di 83 - SpringerBriefs in Computer Science
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Serie: SpringerBriefs in Computer Science, Libro 15 di 83. Libro 15 di 83 - SpringerBriefs in Computer Science
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Paperback. Condizione: Brand New. 81 pages. 9.25x6.10x0.17 inches. In Stock.
Lingua: Inglese
Editore: Springer 2022
Serie: SpringerBriefs in Computer Science, Libro 15 di 83. Libro 15 di 83 - SpringerBriefs in Computer Science
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Paperback. Condizione: new. Paperback. 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 le…arning 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Lingua: Inglese
Editore: Springer, Springer 2022
Serie: SpringerBriefs in Computer Science, Libro 15 di 83. Libro 15 di 83 - SpringerBriefs in Computer Science
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
Altre immaginiLingua: Inglese
Editore: Springer 2022
Serie: SpringerBriefs in Computer Science, Libro 15 di 83. Libro 15 di 83 - SpringerBriefs in Computer Science
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Taschenbuch. Condizione: Neu. Bringing Machine Learning to Software-Defined Networks | Zehua Guo | Taschenbuch | xiii | Englisch | 2022 | Springer | EAN 9789811948732 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Lingua: Inglese
Editore: Springer Nature Singapore 2022
Serie: SpringerBriefs in Computer Science, Libro 15 di 83. Libro 15 di 83 - SpringerBriefs in Computer Science
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Condizione: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | 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 Networkin…g (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.
Lingua: Inglese
Editore: Springer 2022
Serie: SpringerBriefs in Computer Science, Libro 15 di 83. Libro 15 di 83 - SpringerBriefs in Computer Science
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Condizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Springer Nature Singapore Okt 2022 2022
Serie: SpringerBriefs in Computer Science, Libro 15 di 83. Libro 15 di 83 - SpringerBriefs in Computer Science
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 N…etworking (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. 84 pp. Englisch.
Lingua: Inglese
Editore: Springer 2022
Serie: SpringerBriefs in Computer Science, Libro 15 di 83. Libro 15 di 83 - SpringerBriefs in Computer Science
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Lingua: Inglese
Editore: Springer, Berlin|Springer Nature Singapore|Springer 2022
Serie: SpringerBriefs in Computer Science, Libro 15 di 83. Libro 15 di 83 - SpringerBriefs in Computer Science
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 Sof…tware-Defined Networking (SDN). It will a.
Lingua: Inglese
Editore: Springer, Springer Okt 2022 2022
Serie: SpringerBriefs in Computer Science, Libro 15 di 83. Libro 15 di 83 - SpringerBriefs in Computer Science
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Da: buchversandmimpf2000, Emtmannsberg, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 Netwo…rking (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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 84 pp. Englisch.
