Machine Learning Empowered Intelligent Data Center Networking
Machine Learning Empowered Intelligent Data Center Networking

Author: Ting Wang

Publisher: Springer Nature

Published: 2023-02-21

Total Pages: 123

ISBN-13: 9811973954

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An Introduction to the Machine Learning Empowered Intelligent Data Center Networking Fundamentals of Machine Learning in Data Center Networks. This book reviews the common learning paradigms that are widely used in data centernetworks, and offers an introduction to data collection and data processing in data centers. Additionally, it proposes a multi-dimensional and multi-perspective solution quality assessment system called REBEL-3S. The book offers readers a solid foundation for conducting research in the field of AI-assisted data center networks. Comprehensive Survey of AI-assisted Intelligent Data Center Networks. This book comprehensively investigates the peer-reviewed literature published in recent years. The wide range of machine learning techniques is fully reflected to allow fair comparisons. In addition, the book provides in-depth analysis and enlightening discussions on the effectiveness of AI in DCNs from various perspectives, covering flow prediction, flow classification, load balancing, resource management, energy management, routing optimization, congestion control, fault management, and network security. Provides a Broad Overview with Key Insights. This book introduces several novel intelligent networking concepts pioneered by real-world industries, such as Knowledge Defined Networks, Self-Driving Networks, Intent-driven Networks and Intent-based Networks. Moreover, it shares unique insights into the technological evolution of the fusion of artificial intelligence and data center networks, together with selected challenges and future research opportunities.

Machine Learning Empowered Intelligent Data Center Networking
Machine Learning Empowered Intelligent Data Center Networking

Author: Ting Wang

Publisher: Springer

Published: 2023-02-22

Total Pages: 0

ISBN-13: 9789811973949

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An Introduction to the Machine Learning Empowered Intelligent Data Center Networking Fundamentals of Machine Learning in Data Center Networks. This book reviews the common learning paradigms that are widely used in data centernetworks, and offers an introduction to data collection and data processing in data centers. Additionally, it proposes a multi-dimensional and multi-perspective solution quality assessment system called REBEL-3S. The book offers readers a solid foundation for conducting research in the field of AI-assisted data center networks. Comprehensive Survey of AI-assisted Intelligent Data Center Networks. This book comprehensively investigates the peer-reviewed literature published in recent years. The wide range of machine learning techniques is fully reflected to allow fair comparisons. In addition, the book provides in-depth analysis and enlightening discussions on the effectiveness of AI in DCNs from various perspectives, covering flow prediction, flow classification, load balancing, resource management, energy management, routing optimization, congestion control, fault management, and network security. Provides a Broad Overview with Key Insights. This book introduces several novel intelligent networking concepts pioneered by real-world industries, such as Knowledge Defined Networks, Self-Driving Networks, Intent-driven Networks and Intent-based Networks. Moreover, it shares unique insights into the technological evolution of the fusion of artificial intelligence and data center networks, together with selected challenges and future research opportunities.

AI and Machine Learning for Network and Security Management
AI and Machine Learning for Network and Security Management

Author: Yulei Wu

Publisher: John Wiley & Sons

Published: 2022-11-08

Total Pages: 308

ISBN-13: 1119835879

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AI AND MACHINE LEARNING FOR NETWORK AND SECURITY MANAGEMENT Extensive Resource for Understanding Key Tasks of Network and Security Management AI and Machine Learning for Network and Security Management covers a range of key topics of network automation for network and security management, including resource allocation and scheduling, network planning and routing, encrypted traffic classification, anomaly detection, and security operations. In addition, the authors introduce their large-scale intelligent network management and operation system and elaborate on how the aforementioned areas can be integrated into this system, plus how the network service can benefit. Sample ideas covered in this thought-provoking work include: How cognitive means, e.g., knowledge transfer, can help with network and security management How different advanced AI and machine learning techniques can be useful and helpful to facilitate network automation How the introduced techniques can be applied to many other related network and security management tasks Network engineers, content service providers, and cybersecurity service providers can use AI and Machine Learning for Network and Security Management to make better and more informed decisions in their areas of specialization. Students in a variety of related study programs will also derive value from the work by gaining a base understanding of historical foundational knowledge and seeing the key recent developments that have been made in the field.

Cloud Native Data Center Networking
Cloud Native Data Center Networking

Author: Dinesh G. Dutt

Publisher: "O'Reilly Media, Inc."

Published: 2019-11-22

Total Pages: 429

ISBN-13: 1492045551

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If you want to study, build, or simply validate your thinking about modern cloud native data center networks, this is your book. Whether you’re pursuing a multitenant private cloud, a network for running machine learning, or an enterprise data center, author Dinesh Dutt takes you through the steps necessary to design a data center that’s affordable, high capacity, easy to manage, agile, and reliable. Ideal for network architects, data center operators, and network and containerized application developers, this book mixes theory with practice to guide you through the architecture and protocols you need to create and operate a robust, scalable network infrastructure. The book offers a vendor-neutral way to look at network design. For those interested in open networking, this book is chock-full of examples using open source software, from FRR to Ansible. In the context of a cloud native data center, you’ll examine: Clos topology Network disaggregation Network operating system choices Routing protocol choices Container networking Network virtualization and EVPN Network automation

Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning
Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning

Author: Sawyer D. Campbell

Publisher: John Wiley & Sons

Published: 2023-09-26

Total Pages: 596

ISBN-13: 1119853893

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Authoritative reference on the state of the art in the field with additional coverage of important foundational concepts Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning presents cutting-edge research advances in the rapidly growing areas in optical and RF electromagnetic device modeling, simulation, and inverse-design. The text provides a comprehensive treatment of the field on subjects ranging from fundamental theoretical principles and new technological developments to state-of-the-art device design, as well as examples encompassing a wide range of related sub-areas. The content of the book covers all-dielectric and metallodielectric optical metasurface deep learning-accelerated inverse-design, deep neural networks for inverse scattering, applications of deep learning for advanced antenna design, and other related topics. To aid in reader comprehension, each chapter contains 10-15 illustrations, including prototype photos, line graphs, and electric field plots. Contributed to by leading research groups in the field, sample topics covered in Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning include: Optical and photonic design, including generative machine learning for photonic design and inverse design of electromagnetic systems RF and antenna design, including artificial neural networks for parametric electromagnetic modeling and optimization and analysis of uniform and non-uniform antenna arrays Inverse scattering, target classification, and other applications, including deep learning for high contrast inverse scattering of electrically large structures Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning is a must-have resource on the topic for university faculty, graduate students, and engineers within the fields of electromagnetics, wireless communications, antenna/RF design, and photonics, as well as researchers at large defense contractors and government laboratories.

Fog Radio Access Networks (F-RAN)
Fog Radio Access Networks (F-RAN)

Author: Mugen Peng

Publisher: Springer Nature

Published: 2020-08-12

Total Pages: 227

ISBN-13: 3030507351

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This book provides a comprehensive introduction of Fog Radio Access Networks (F-RANs), from both academic and industry perspectives. The authors first introduce the network architecture and the frameworks of network management and resource allocation for F-RANs. They then discuss the recent academic research achievements of F-RANs, such as the analytical results of theoretical performance limits and optimization theory-based resource allocation techniques. Meanwhile, they discuss the application and implementations of F-RANs, including the latest standardization procedure, and the prototype and test bed design. The book is concluded by summarizing the existing open issues and future trends of F-RANs. Includes the latest theoretical and technological research achievements of F-RANs, also discussing existing open issues and future trends of F-RANs toward 6G from an interdisciplinary perspective; Provides commonly-used tools for research and development of F-RANs such as open resource projects for implementing prototypes and test beds; Includes examples of prototype and test bed design and gives tools to evaluate the performance of F-RANs in simulations and experimental circumstances.

Data-Driven Mining, Learning and Analytics for Secured Smart Cities
Data-Driven Mining, Learning and Analytics for Secured Smart Cities

Author: Chinmay Chakraborty

Publisher: Springer Nature

Published: 2021-04-28

Total Pages: 383

ISBN-13: 3030721396

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This book provides information on data-driven infrastructure design, analytical approaches, and technological solutions with case studies for smart cities. This book aims to attract works on multidisciplinary research spanning across the computer science and engineering, environmental studies, services, urban planning and development, social sciences and industrial engineering on technologies, case studies, novel approaches, and visionary ideas related to data-driven innovative solutions and big data-powered applications to cope with the real world challenges for building smart cities.

Fog Computing for Intelligent Cloud IoT Systems
Fog Computing for Intelligent Cloud IoT Systems

Author: Chandan Banerjee

Publisher: John Wiley & Sons

Published: 2024-06-04

Total Pages: 391

ISBN-13: 1394175329

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FOG COMPUTING FOR INTELLIGENT CLOUD IOT SYSTEMS This book is a comprehensive guide on fog computing and how it facilitates computing, storage, and networking services Fog computing is a decentralized computing structure that connects data, devices, and the cloud. It is an extension of cloud computing and is an essential concept in IoT (Internet of Things), as it reduces the burden of processing in cloud computing. It brings intelligence and processing closer to where the data is created and transmitted to other sources. Fog computing has many benefits, such as reduced latency in processing data, better response time that helps the user’s experience, and security and privacy compliance that assures protecting the vital data in the cloud. It also reduces the cost of bandwidth, because the processing is achieved in the cloud, which reduces network bandwidth usage and increases efficiency as user devices share data in the local processing infrastructure rather than the cloud service. Fog computing has various applications across industries, such as agriculture and farming, the healthcare industry, smart cities, education, and entertainment. For example, in the agriculture industry, a very prominent example is the SWAMP project, which stands for Smart Water Management Platform. With fog computing’s help, SWAMP develops a precision-based smart irrigation system concept used in agriculture, minimizing water wastage. This book is divided into three sections. The first section studies fog computing and machine learning, covering fog computing architecture, application perspective, computational offloading in mobile cloud computing, intelligent Cloud-IoT systems, machine learning fundamentals, and data visualization. The second section focuses on applications and analytics, spanning various applications of fog computing, such as in healthcare, Industry 4.0, cancer cell detection systems, smart farming, and precision farming. This section also covers analytics in fog computing using big data and patient monitoring systems, and the emergence of fog computing concerning applications and potentialities in traditional and digital educational systems. Security aspects in fog computing through blockchain and IoT, and fine-grained access through attribute-based encryption for fog computing are also covered. Audience The book will be read by researchers and engineers in computer science, information technology, electronics, and communication specializing in machine learning, deep learning, the cyber world, IoT, and security systems.

World Of 5g, The (In 5 Volumes)
World Of 5g, The (In 5 Volumes)

Author:

Publisher: World Scientific

Published: 2022-04-07

Total Pages: 736

ISBN-13: 9811250197

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5G is becoming a critically important supporting technology for industrial evolvement.The World of 5G series consists of five salient volumes — Internet of Everything, Intelligent Manufacturing, Intelligent Home, Intelligent Transportation, and Intelligent Medicine.Aim to capture new opportunities brought by 5G, this compendium set focuses on the key technologies, requirements, users' experiences, industry applications, and industrial reforms from the perspective of experts, and comprehensively introduces the related knowledge of 5G.These reference volumes inform readers the essences of 5G, potential changes to the development of public life and society brought by 5G, as well as the potential security and risks such as the legal, moral and ethical aspects.The set also prominently reflects the latest business status in different industrial and social fields, and the great changes that follow.

World Of 5g, The - Volume 1: Internet Of Everything
World Of 5g, The - Volume 1: Internet Of Everything

Author: Wenquan Che

Publisher: World Scientific

Published: 2022-04-07

Total Pages: 143

ISBN-13: 9811244154

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5th Generation (5G) technology has been regarded as a critically important supporting technology for industrial evolution. This book begins by tracing the development of 5G mobile communication, including the characteristics and limitations of different editions.It then covers the technical characteristics of 5G and its possible potential applications in every aspect of our lives, as well as projections of lives after 5G.Further to the technical introduction, the authors also look into the social domination of 5G technology and its implications.