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Machine Learning Empowered Intelligent Data Center Networking

Ting Wang,Bo Li,Mingsong Chen,Shui Yu

Author : Ting Wang,Bo Li,Mingsong Chen,Shui Yu
Publisher : Springer
Page : 0 pages
File Size : 49,6 Mb
Release : 2023-02-22
Category : Computers
ISBN : 9811973946

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Machine Learning Empowered Intelligent Data Center Networking by Ting Wang,Bo Li,Mingsong Chen,Shui Yu Pdf

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

Ting Wang,Bo Li,Mingsong Chen,Shui Yu

Author : Ting Wang,Bo Li,Mingsong Chen,Shui Yu
Publisher : Springer Nature
Page : 123 pages
File Size : 45,8 Mb
Release : 2023-02-21
Category : Computers
ISBN : 9789811973956

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Machine Learning Empowered Intelligent Data Center Networking by Ting Wang,Bo Li,Mingsong Chen,Shui Yu Pdf

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.

Artificial Intelligence for Autonomous Networks

Mazin Gilbert

Author : Mazin Gilbert
Publisher : CRC Press
Page : 498 pages
File Size : 50,5 Mb
Release : 2018-09-25
Category : Computers
ISBN : 9781351130141

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Artificial Intelligence for Autonomous Networks by Mazin Gilbert Pdf

Artificial Intelligence for Autonomous Networks introduces the autonomous network by juxtaposing two unique technologies and communities: Networking and AI. The book reviews the technologies behind AI and software-defined network/network function virtualization, highlighting the exciting opportunities to integrate those two worlds. Outlining the new frontiers for autonomous networks, this book highlights their impact and benefits to consumers and enterprise customers. It also explores the potential of the autonomous network for transforming network operation, cyber security, enterprise services, 5G and IoT, infrastructure monitoring and traffic optimization, and finally, customer experience and care. With contributions from leading experts, this book will provide an invaluable resource for network engineers, software engineers, artificial intelligence, and machine learning researchers.

Artificial Intelligence to Solve Pervasive Internet of Things Issues

Gurjit Kaur,Pradeep Tomar,Marcus Tanque

Author : Gurjit Kaur,Pradeep Tomar,Marcus Tanque
Publisher : Academic Press
Page : 430 pages
File Size : 44,6 Mb
Release : 2020-11-18
Category : Science
ISBN : 9780128196984

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Artificial Intelligence to Solve Pervasive Internet of Things Issues by Gurjit Kaur,Pradeep Tomar,Marcus Tanque Pdf

Artificial Intelligence to Solve Pervasive Internet of Things Issues discusses standards and technologies and wide-ranging technology areas and their applications and challenges, including discussions on architectures, frameworks, applications, best practices, methods and techniques required for integrating AI to resolve IoT issues. Chapters also provide step-by-step measures, practices and solutions to tackle vital decision-making and practical issues affecting IoT technology, including autonomous devices and computerized systems. Such issues range from adopting, mitigating, maintaining, modernizing and protecting AI and IoT infrastructure components such as scalability, sustainability, latency, system decentralization and maintainability. The book enables readers to explore, discover and implement new solutions for integrating AI to solve IoT issues. Resolving these issues will help readers address many real-world applications in areas such as scientific research, healthcare, defense, aeronautics, engineering, social media, and many others. Discusses intelligent techniques for the implementation of Artificial Intelligence in Internet of Things Prepared for researchers and specialists who are interested in the use and integration of IoT and Artificial Intelligence technologies

Implementing Data Analytics and Architectures for Next Generation Wireless Communications

Bhatt, Chintan,Kumar, Neeraj,Bashir, Ali Kashif,Alazab, Mamoun

Author : Bhatt, Chintan,Kumar, Neeraj,Bashir, Ali Kashif,Alazab, Mamoun
Publisher : IGI Global
Page : 227 pages
File Size : 55,8 Mb
Release : 2021-08-13
Category : Technology & Engineering
ISBN : 9781799869900

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Implementing Data Analytics and Architectures for Next Generation Wireless Communications by Bhatt, Chintan,Kumar, Neeraj,Bashir, Ali Kashif,Alazab, Mamoun Pdf

Wireless communication is continuously evolving to improve and be a part of our daily communication. This leads to improved quality of services and applications supported by networking technologies. We are now able to use LTE, LTE-Advanced, and other emerging technologies due to the enormous efforts that are made to improve the quality of service in cellular networks. As the future of networking is uncertain, the use of deep learning and big data analytics is a point of focus as it can work in many capacities at a variety of levels for wireless communications. Implementing Data Analytics and Architectures for Next Generation Wireless Communications addresses the existing and emerging theoretical and practical challenges in the design, development, and implementation of big data algorithms, protocols, architectures, and applications for next generation wireless communications and their applications in smart cities. The chapters of this book bring together academics and industrial practitioners to exchange, discuss, and implement the latest innovations and applications of data analytics in advanced networks. Specific topics covered include key encryption techniques, smart home appliances, fog communication networks, and security in the internet of things. This book is valuable for technologists, data analysts, networking experts, practitioners, researchers, academicians, and students.

Developing Networks using Artificial Intelligence

Haipeng Yao,Chunxiao Jiang,Yi Qian

Author : Haipeng Yao,Chunxiao Jiang,Yi Qian
Publisher : Springer
Page : 248 pages
File Size : 50,7 Mb
Release : 2019-04-26
Category : Technology & Engineering
ISBN : 9783030150280

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Developing Networks using Artificial Intelligence by Haipeng Yao,Chunxiao Jiang,Yi Qian Pdf

This book mainly discusses the most important issues in artificial intelligence-aided future networks, such as applying different ML approaches 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 learning-based traffic awareness algorithms, such as traffic classification, anomaly traffic identification and traffic prediction. The authors introduce some ML approaches like reinforcement learning to deal with network control problem in this book. Traditional works on the control plane largely rely on a manual process in configuring forwarding, which cannot be employed for today's network conditions. To address this issue, several artificial intelligence approaches for self-learning control strategies are introduced. In addition, resource management problems are ubiquitous in the networking field, such as job scheduling, bitrate adaptation in video streaming and virtual machine placement in cloud computing. Compared with the traditional with-box approach, the authors present some ML methods to solve the complexity network resource allocation problems. Finally, semantic comprehension function is introduced to the network to understand the high-level business intent in this book. With Software-Defined Networking (SDN), Network Function Virtualization (NFV), 5th Generation Wireless Systems (5G) development, the global network is undergoing profound restructuring and transformation. However, with the improvement of the flexibility and scalability of the networks, as well as the ever-increasing complexity of networks, makes effective monitoring, overall control, and optimization of the network extremely difficult. Recently, adding intelligence to the control plane through AI&ML become a trend and a direction of network development This book's expected audience includes professors, researchers, scientists, practitioners, engineers, industry managers, and government research workers, who work in the fields of intelligent network. Advanced-level students studying computer science and electrical engineering will also find this book useful as a secondary textbook.

IoT and Big Data Technologies for Health Care

Shuihua Wang,Zheng Zhang,Yuan Xu

Author : Shuihua Wang,Zheng Zhang,Yuan Xu
Publisher : Springer Nature
Page : 600 pages
File Size : 40,7 Mb
Release : 2022-06-17
Category : Medical
ISBN : 9783030941857

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IoT and Big Data Technologies for Health Care by Shuihua Wang,Zheng Zhang,Yuan Xu Pdf

This two-volume set of LNICST 414 and 415 constitutes the refereed post-conference proceedings of the 2nd International Conference on IoT and Big Data Technologies for Health Care, IoTCARE 2021, which took place in October 2021. Due to COVID-19 pandemic the conference was held virtually. The 79 revised full papers were carefully reviewed and selected from 165 submissions. The papers are arranged thematically as follows: Integrating healthcare with IoT; Information fusion for the devices of IoT; AI-based internet of medical things.

Big Data and Computational Intelligence in Networking

Yulei Wu,Fei Hu,Geyong Min,Albert Y. Zomaya

Author : Yulei Wu,Fei Hu,Geyong Min,Albert Y. Zomaya
Publisher : CRC Press
Page : 530 pages
File Size : 49,5 Mb
Release : 2017-12-14
Category : Computers
ISBN : 9781498784870

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Big Data and Computational Intelligence in Networking by Yulei Wu,Fei Hu,Geyong Min,Albert Y. Zomaya Pdf

This book presents state-of-the-art solutions to the theoretical and practical challenges stemming from the leverage of big data and its computational intelligence in supporting smart network operation, management, and optimization. In particular, the technical focus covers the comprehensive understanding of network big data, efficient collection and management of network big data, distributed and scalable online analytics for network big data, and emerging applications of network big data for computational intelligence.

Bringing Machine Learning to Software-Defined Networks

Zehua Guo

Author : Zehua Guo
Publisher : Springer Nature
Page : 78 pages
File Size : 40,9 Mb
Release : 2022-10-05
Category : Computers
ISBN : 9789811948749

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Bringing Machine Learning to Software-Defined Networks by Zehua Guo Pdf

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.

Sustainable Advanced Computing

Sagaya Aurelia,Somashekhar S. Hiremath,Karthikeyan Subramanian,Saroj Kr. Biswas

Author : Sagaya Aurelia,Somashekhar S. Hiremath,Karthikeyan Subramanian,Saroj Kr. Biswas
Publisher : Springer Nature
Page : 669 pages
File Size : 47,5 Mb
Release : 2022-03-30
Category : Technology & Engineering
ISBN : 9789811690129

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Sustainable Advanced Computing by Sagaya Aurelia,Somashekhar S. Hiremath,Karthikeyan Subramanian,Saroj Kr. Biswas Pdf

This volume presents select proceedings of the International Conference on Sustainable Advanced Computing (ICSAC – 2021). It covers the latest research on a wide range of topics spanning theory, systems, applications, and case studies in advanced computing. Topics covered are machine intelligence, expert systems, robotics, natural language processing, cognitive science, quantum computing, deep learning, pattern recognition, human-computer interface, biometrics, graph theory, etc. The volume focuses on the novel research findings and innovations of various researchers. In addition, the book will be a promising solution for new generation-based sustainable, intelligent systems that are machine and human-centered with modern models and appropriate amalgamations of collaborative practices with a general objective of better research in all aspects of sustainable advanced computing.

AI and Machine Learning for Network and Security Management

Yulei Wu,Jingguo Ge,Tong Li

Author : Yulei Wu,Jingguo Ge,Tong Li
Publisher : John Wiley & Sons
Page : 308 pages
File Size : 54,5 Mb
Release : 2022-11-08
Category : Computers
ISBN : 9781119835875

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AI and Machine Learning for Network and Security Management by Yulei Wu,Jingguo Ge,Tong Li Pdf

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.

Artificial Intelligence and Security

Xingming Sun,Xiaorui Zhang,Zhihua Xia,Elisa Bertino

Author : Xingming Sun,Xiaorui Zhang,Zhihua Xia,Elisa Bertino
Publisher : Springer Nature
Page : 701 pages
File Size : 52,9 Mb
Release : 2022-07-04
Category : Computers
ISBN : 9783031067884

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Artificial Intelligence and Security by Xingming Sun,Xiaorui Zhang,Zhihua Xia,Elisa Bertino Pdf

This three-volume set LNCS 13338-13340 constitutes the thoroughly refereed proceedings of the 8th International Conference on Artificial Intelligence and Security, ICAIS 2022, which was held in Qinghai, China, in July 2022. The total of 166 papers included in the 3 volumes were carefully reviewed and selected from 1124 submissions. The papers present research, development, and applications in the fields of artificial intelligence and information security

Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning

Sawyer D. Campbell,Douglas H. Werner

Author : Sawyer D. Campbell,Douglas H. Werner
Publisher : John Wiley & Sons
Page : 596 pages
File Size : 51,9 Mb
Release : 2023-09-26
Category : Technology & Engineering
ISBN : 9781119853893

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Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning by Sawyer D. Campbell,Douglas H. Werner Pdf

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.

Heterogenous Computational Intelligence in Internet of Things

Pawan Singh,Prateek Singhal,Pramod Kumar Mishra,Avimanyou K. Vatsa

Author : Pawan Singh,Prateek Singhal,Pramod Kumar Mishra,Avimanyou K. Vatsa
Publisher : CRC Press
Page : 376 pages
File Size : 49,9 Mb
Release : 2023-10-23
Category : Computers
ISBN : 9781000967944

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Heterogenous Computational Intelligence in Internet of Things by Pawan Singh,Prateek Singhal,Pramod Kumar Mishra,Avimanyou K. Vatsa Pdf

We have seen a sharp increase in the development of data transfer techniques in the networking industry over the past few years. We can see that the photos are assisting clinicians in detecting infection in patients even in the current COVID-19 pandemic condition. With the aid of ML/AI, medical imaging, such as lung X-rays for COVID-19 infection, is crucial in the early detection of many diseases. We also learned that in the COVID-19 scenario, both wired and wireless networking are improved for data transfer but have network congestion. An intriguing concept that has the ability to reduce spectrum congestion and continuously offer new network services is providing wireless network virtualization. The degree of virtualization and resource sharing varies between the paradigms. Each paradigm has both technical and non-technical issues that need to be handled before wireless virtualization becomes a common technology. For wireless network virtualization to be successful, these issues need careful design and evaluation. Future wireless network architecture must adhere to a number of Quality of Service (QoS) requirements. Virtualization has been extended to wireless networks as well as conventional ones. By enabling multi-tenancy and tailored services with a wider range of carrier frequencies, it improves efficiency and utilization. In the IoT environment, wireless users are heterogeneous, and the network state is dynamic, making network control problems extremely difficult to solve as dimensionality and computational complexity keep rising quickly. Deep Reinforcement Learning (DRL) has been developed by the use of Deep Neural Networks (DNNs) as a potential approach to solve high-dimensional and continuous control issues effectively. Deep Reinforcement Learning techniques provide great potential in IoT, edge and SDN scenarios and are used in heterogeneous networks for IoT-based management on the QoS required by each Software Defined Network (SDN) service. While DRL has shown great potential to solve emerging problems in complex wireless network virtualization, there are still domain-specific challenges that require further study, including the design of adequate DNN architectures with 5G network optimization issues, resource discovery and allocation, developing intelligent mechanisms that allow the automated and dynamic management of the virtual communications established in the SDNs which is considered as research perspective.

Cloud Native Data Center Networking

Dinesh G. Dutt

Author : Dinesh G. Dutt
Publisher : O'Reilly Media
Page : 486 pages
File Size : 52,5 Mb
Release : 2019-11-22
Category : Computers
ISBN : 9781492045571

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Cloud Native Data Center Networking by Dinesh G. Dutt Pdf

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

Machine Learning Empowered Intelligent Data Center Networking

Machine Learning Empowered Intelligent Data Center Networking by Ting Wang,Bo Li,Mingsong Chen,Shui Yu Pdf

Machine Learning Empowered Intelligent Data Center Networking by Ting Wang,Bo Li,Mingsong Chen,Shui Yu Pdf

Artificial Intelligence for Autonomous Networks by Mazin Gilbert Pdf

Artificial Intelligence to Solve Pervasive Internet of Things Issues by Gurjit Kaur,Pradeep Tomar,Marcus Tanque Pdf

Implementing Data Analytics and Architectures for Next Generation Wireless Communications by Bhatt, Chintan,Kumar, Neeraj,Bashir, Ali Kashif,Alazab, Mamoun Pdf

Developing Networks using Artificial Intelligence by Haipeng Yao,Chunxiao Jiang,Yi Qian Pdf

IoT and Big Data Technologies for Health Care by Shuihua Wang,Zheng Zhang,Yuan Xu Pdf

Big Data and Computational Intelligence in Networking by Yulei Wu,Fei Hu,Geyong Min,Albert Y. Zomaya Pdf

Bringing Machine Learning to Software-Defined Networks by Zehua Guo Pdf

Sustainable Advanced Computing by Sagaya Aurelia,Somashekhar S. Hiremath,Karthikeyan Subramanian,Saroj Kr. Biswas Pdf

AI and Machine Learning for Network and Security Management by Yulei Wu,Jingguo Ge,Tong Li Pdf

Artificial Intelligence and Security by Xingming Sun,Xiaorui Zhang,Zhihua Xia,Elisa Bertino Pdf

Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning by Sawyer D. Campbell,Douglas H. Werner Pdf

Heterogenous Computational Intelligence in Internet of Things by Pawan Singh,Prateek Singhal,Pramod Kumar Mishra,Avimanyou K. Vatsa Pdf

Cloud Native Data Center Networking by Dinesh G. Dutt Pdf

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