Machine Learning Empowered Intelligent Data Center Networking

Author : Ting Wang
Publisher : Springer
ISBN 13 : 9789811973949
Total Pages : 0 pages
Book Rating : 4.46/5 ( download)

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Download or read book Machine Learning Empowered Intelligent Data Center Networking written by Ting Wang and published by Springer. This book was released on 2023-02-22 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : Ting Wang
Publisher : Springer Nature
ISBN 13 : 9811973954
Total Pages : 123 pages
Book Rating : 4.56/5 ( download)

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Download or read book Machine Learning Empowered Intelligent Data Center Networking written by Ting Wang and published by Springer Nature. This book was released on 2023-02-21 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : Mazin Gilbert
Publisher : CRC Press
ISBN 13 : 1351130145
Total Pages : 498 pages
Book Rating : 4.41/5 ( download)

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Download or read book Artificial Intelligence for Autonomous Networks written by Mazin Gilbert and published by CRC Press. This book was released on 2018-09-25 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : Gurjit Kaur
Publisher : Academic Press
ISBN 13 : 012819698X
Total Pages : 430 pages
Book Rating : 4.84/5 ( download)

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Download or read book Artificial Intelligence to Solve Pervasive Internet of Things Issues written by Gurjit Kaur and published by Academic Press. This book was released on 2020-11-18 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Author : Bhatt, Chintan
Publisher : IGI Global
ISBN 13 : 1799869903
Total Pages : 227 pages
Book Rating : 4.00/5 ( download)

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Download or read book Implementing Data Analytics and Architectures for Next Generation Wireless Communications written by Bhatt, Chintan and published by IGI Global. This book was released on 2021-08-13 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : Shuihua Wang
Publisher : Springer Nature
ISBN 13 : 303094185X
Total Pages : 600 pages
Book Rating : 4.57/5 ( download)

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Download or read book IoT and Big Data Technologies for Health Care written by Shuihua Wang and published by Springer Nature. This book was released on 2022-06-17 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : Zehua Guo
Publisher : Springer Nature
ISBN 13 : 9811948747
Total Pages : 78 pages
Book Rating : 4.49/5 ( download)

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Download or read book Bringing Machine Learning to Software-Defined Networks written by Zehua Guo and published by Springer Nature. This book was released on 2022-10-05 with total page 78 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : Haipeng Yao
Publisher : Springer
ISBN 13 : 3030150283
Total Pages : 248 pages
Book Rating : 4.80/5 ( download)

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Download or read book Developing Networks using Artificial Intelligence written by Haipeng Yao and published by Springer. This book was released on 2019-04-26 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : Sagaya Aurelia
Publisher : Springer Nature
ISBN 13 : 981169012X
Total Pages : 669 pages
Book Rating : 4.29/5 ( download)

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Download or read book Sustainable Advanced Computing written by Sagaya Aurelia and published by Springer Nature. This book was released on 2022-03-30 with total page 669 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : Yulei Wu
Publisher : CRC Press
ISBN 13 : 1498784879
Total Pages : 530 pages
Book Rating : 4.70/5 ( download)

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Download or read book Big Data and Computational Intelligence in Networking written by Yulei Wu and published by CRC Press. This book was released on 2017-12-14 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.