Artificial Intelligence For Autonomous Networks
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Artificial Intelligence For Autonomous Networks
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Author : Mazin Gilbert
language : en
Publisher: CRC Press
Release Date : 2018-09-25
Artificial Intelligence For Autonomous Networks written by Mazin Gilbert and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-25 with Computers categories.
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.
Towards Cognitive Autonomous Networks
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Author : Stephen S. Mwanje
language : en
Publisher: John Wiley & Sons
Release Date : 2020-10-12
Towards Cognitive Autonomous Networks written by Stephen S. Mwanje and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-12 with Technology & Engineering categories.
Learn about the latest in cognitive and autonomous network management Towards Cognitive Autonomous Networks: Network Management Automation for 5G and Beyond delivers a comprehensive understanding of the current state-of-the-art in cognitive and autonomous network operation. Authors Mwanje and Bell fully describe todays capabilities while explaining the future potential of these powerful technologies. This book advocates for autonomy in new 5G networks, arguing that the virtualization of network functions render autonomy an absolute necessity. Following that, the authors move on to comprehensively explain the background and history of large networks, and how we come to find ourselves in the place were in now. Towards Cognitive Autonomous Networks describes several novel techniques and applications of cognition and autonomy required for end-to-end cognition including: • Configuration of autonomous networks • Operation of autonomous networks • Optimization of autonomous networks • Self-healing autonomous networks The book concludes with an examination of the extensive challenges facing completely autonomous networks now and in the future.
Autonomous Driving Network
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Author : Wenshuan Dang
language : en
Publisher: CRC Press
Release Date : 2024-01-15
Autonomous Driving Network written by Wenshuan Dang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-15 with Computers categories.
Aiming to outline the vision of realizing automated and intelligent communication networks in the era of intelligence, this book describes the development history, application scenarios, theories, architectures, and key technologies of Huawei's Autonomous Driving Network (ADN) solution. In the book, the authors explain the design of the top-level architecture, hierarchical architecture (ANE, NetGraph, and AI Native NE), and key feature architecture (distributed AI and endogenous security) that underpin Huawei's ADN solution. The book delves into various key technologies, including trustworthy AI, distributed AI, digital twin, network simulation, digitization of knowledge and expertise, human-machine symbiosis, NE endogenous intelligence, and endogenous security. It also provides an overview of the standards and level evaluation methods defined by industry and standards organizations, and uses Huawei's ADN solution as an example to illustrate how to implement AN. This book is an essential reference for professionals and researchers who want to gain a deeper understanding of automated and intelligent communication networks and their applications.
Explainable Ai For Communications And Networking
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Author : Hatim Chergui
language : en
Publisher: Academic Press
Release Date : 2025-04-18
Explainable Ai For Communications And Networking written by Hatim Chergui and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-18 with Technology & Engineering categories.
Explainable AI for Communications and Networking: Toward Responsible Automation gives a tour into the realm of Explainable Artificial Intelligence (XAI) and its impact on transparent and autonomous communication networks. The book equips readers from diverse backgrounds in communications and networking with a variety of XAI tools, metrics and frameworks to demystify AI systems through graphical taxonomies and mathematical formulations, which are further enriched with code snippets. The book also examines XAI implementation in wireless communications, network management, generative AI for telecom and cybersecurity, before presenting practical use-cases emanating from an industry perspective. Finally, the regulatory, ethical, and legal implications of XAI in telecommunications are reviewed, before concluding with key challenges and takeaways. - Includes XAI graphical taxonomies, metrics, formulations and code snippets. - Provides practical examples and use-cases from a telecom industry perspective. - Covers implementation guidelines (XAI libraries/implementation tools) tailored to a communications and networking context. - Highlights the application of XAI in wireless communications, network management, generative AI for telecom and cybersecurity. - Presents a thorough synthesis of the regulatory and ethical implications of XAI worldwide.
Towards Cognitive Autonomous Networks
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Author : Stephen S. Mwanje
language : en
Publisher: John Wiley & Sons
Release Date : 2020-10-12
Towards Cognitive Autonomous Networks written by Stephen S. Mwanje and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-12 with Technology & Engineering categories.
Learn about the latest in cognitive and autonomous network management Towards Cognitive Autonomous Networks: Network Management Automation for 5G and Beyond delivers a comprehensive understanding of the current state-of-the-art in cognitive and autonomous network operation. Authors Mwanje and Bell fully describe todays capabilities while explaining the future potential of these powerful technologies. This book advocates for autonomy in new 5G networks, arguing that the virtualization of network functions render autonomy an absolute necessity. Following that, the authors move on to comprehensively explain the background and history of large networks, and how we come to find ourselves in the place were in now. Towards Cognitive Autonomous Networks describes several novel techniques and applications of cognition and autonomy required for end-to-end cognition including: • Configuration of autonomous networks • Operation of autonomous networks • Optimization of autonomous networks • Self-healing autonomous networks The book concludes with an examination of the extensive challenges facing completely autonomous networks now and in the future.
Handbook Of Research Of Internet Of Things And Cyber Physical Systems
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Author : Amit Kumar Tyagi
language : en
Publisher: CRC Press
Release Date : 2022-06-08
Handbook Of Research Of Internet Of Things And Cyber Physical Systems written by Amit Kumar Tyagi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-08 with Computers categories.
This new volume discusses how integrating IoT devices and cyber-physical systems can help society by providing multiple efficient and affordable services to users. It covers the various applications of IoT-based cyber-physical systems, such as satellite imaging in relation to climate change, industrial control systems, e-healthcare applications, security uses, automotive and traffic monitoring and control, urban smart city planning, and more. The authors also outline the methods, tools, and algorithms for IoT-based cyber-physical systems and explore the integration of machine learning, blockchain, and Internet of Things-based cloud applications. With the continuous emerging new technologies and trends in IoT technology and CPS, this volume will be a helpful resource for scientists, researchers, industry professionals, faculty and students, and others who wish to keep abreast of new developments and new challenges for sustainable development in Industry 4.0.
Revolutionizing Network Management The Journey To Ai Native Autonomy
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Author : Csaba Vulkán
language : en
Publisher: CRC Press
Release Date : 2025-12-09
Revolutionizing Network Management The Journey To Ai Native Autonomy written by Csaba Vulkán and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-12-09 with Computers categories.
End-to-end automation in telecommunications is a challenging yet critical industry objective, representing collective vision for technology evolution in the coming years. Key enablers for achieving this include the expression and the translation of high-level business goals (e.g. intents) into actionable and impactful operations, the deployment and interaction between closed loops, real-time data management, the extraction of meaningful insights from data, ML-driven analytics and intelligence, and seamless orchestration and resource control. Automation processes must be transparent, reliable and robust. This book provides a comprehensive insight into the automation journey. It explores the vision of zero-touch, AI-native network and service autonomy, examining the key trends, catalysts, and technological advancements shaping this paradigm shift. It provides a comprehensive analysis of critical aspects such as data and knowledge management, security and trust, native AI/ML management, intent-based automation, and human-to-machine as well as machine-to-machine interfaces. By delving into advanced concepts such as data-driven, AI-powered analytics, semantic and decision models, network digital twins, and the role of natural language processing and large language models, the book bridges theory and practical application. It highlights how these innovations leverage and maximize intent-driven and closed-loop automation, enabling seamless, intelligent, and autonomous networks. Additionally, it identifies key areas where further research is needed to address existing gaps and unlock the full potential of these technologies. Ultimately, this book provides valuable insights, outlining the transformative potential of zero-touch, AI-native networks and paving the way for seamless, intelligent, and autonomous management of networks and services, driving innovation, efficiency, and new opportunities in the evolving digital landscape.
Ai Driven Networks Architecting The Future Of Autonomous Secure And Cloud Native Connectivity 2025
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Author : AUTHOR:1-DIPESH JAGDISH KASHIV, AUTHOR:2-PROF (DR) MOPARTHI NAGESWARA RAO
language : en
Publisher: YASHITA PRAKASHAN PRIVATE LIMITED
Release Date :
Ai Driven Networks Architecting The Future Of Autonomous Secure And Cloud Native Connectivity 2025 written by AUTHOR:1-DIPESH JAGDISH KASHIV, AUTHOR:2-PROF (DR) MOPARTHI NAGESWARA RAO and has been published by YASHITA PRAKASHAN PRIVATE LIMITED this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
PREFACE In an age defined by relentless digital innovation, networks have evolved far beyond simple conduits for data. They now serve as the critical nervous system of entire industries—powering everything from real-time financial transactions to massive Internet-of-Things deployments and immersive 5G applications. Yet the exponential growth in traffic volumes, the dynamic nature of modern applications, and the sophistication of cyber-threats have exposed the limitations of static, manually managed infrastructures. AI-Driven Networks: Architecting the Future of Autonomous, Secure, and Cloud-Native Connectivity was conceived to meet this challenge head-on, providing a comprehensive roadmap for embedding intelligence, resilience, and automation into every layer of the network stack. Our journey begins in Chapter 1: Foundations of AI-Driven Networking, where we introduce the core principles that underpin the fusion of artificial intelligence and networking. After grounding readers in key machine-learning paradigms—supervised, unsupervised, and reinforcement learning—we map these techniques onto fundamental networking functions such as routing, traffic classification, and anomaly detection. Building on these fundamentals, Chapter 2: Intent-Based and Self-Driving Architectures explores how high-level business objectives can be translated into automated network behaviors. By examining intent interfaces—ranging from declarative APIs to natural-language processing tools—we demonstrate how directives like “ensure sub-5 ms latency between our core data centers” can be codified, deployed, and continuously enforced across software-defined networking controllers, routers, and security gateways. In Chapter 3: Data-Plane Intelligence—From Telemetry to Insights, we dive into the lifeblood of AI-driven networks: data. Modern network devices emit rich, high-velocity telemetry streams—flow records, per-queue latency histograms, packet-level metrics—and ingesting, storing, and analyzing this data at scale is a monumental engineering challenge. We detail scalable architectures for real-time telemetry collection, explore unsupervised anomaly-detection models that surface emerging congestion hotspots, and show how predictive analytics can forecast capacity needs hours or days in advance to enable proactive resource scaling. Chapter 4: Control-Plane Optimization with Reinforcement introduces reinforcement learning as the engine for adaptive, closed-loop control. Beginning with tabular Q-Learning methods that dynamically tune link weights in OSPF and segment-routing protocols, we progress to advanced policy-gradient algorithms—REINFORCE and actor-critic variants—that learn to split flows optimally for throughput and fairness. Multi-agent RL scenarios illustrate how multiple controllers, or administrative domains can cooperate or compete to maximize global efficiency, all while honoring strict service-level agreements. Security is woven throughout every chapter, but Chapter 5: Secure by Design—AI for Threat Detection and Response provides an in-depth exploration of zero-trust enforcement and AI-driven defenses. We unpack the “never trust, always verify” paradigm, showing how continuous authentication—powered by behavioral profiling, device-fingerprinting, and contextual risk scoring—can prevent unauthorized lateral movement even after perimeter breaches. AI-based micro-segmentation adapts dynamically to traffic patterns, while deep-learning models detect novel attack vectors. We conclude with frameworks for automated incident response, orchestrating containment actions like host isolation, firewall rule updates, and credential rotations in real time. As networks embrace containerization and cloud-native platforms, Chapter 6: Cloud-Native and Kubernetes Integration examines how microservices design patterns, service meshes, and GitOps workflows can host AI inference engines for fine-grained policy enforcement. We show how Kubernetes CNI plugins incorporate ML models for per-pod traffic classification, how canary deployments can be orchestrated through AI-driven traffic-splitting strategies, and how declarative pipelines ensure safe, auditable policy roll-outs. Subsequent chapters synthesize these advancements into end-to-end automation and observability frameworks (Chapters 7–9), explore the unique opportunities at the network edge and in 5G environments (Chapter 10), peer into the future with quantum networking and post-quantum resilience strategies (Chapter 11), and address the governance, compliance, and ethical considerations that accompany the adoption of autonomous, AI-driven networks (Chapter 12). Whether you are a network architect designing carrier-grade backbones, a security engineer safeguarding mission-critical infrastructure, or a researcher advancing autonomous systems, this book equips you with the theories, tools, and real-world techniques needed to build networks that not only meet today’s demands but also learn, adapt, and scale as the digital landscape evolves. The future of connectivity is intelligent—and it starts here. Authors Dipesh Jagdish Kashiv
Artificial Intelligence Application In Networks And Systems
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Author : Radek Silhavy
language : en
Publisher: Springer Nature
Release Date : 2023-07-08
Artificial Intelligence Application In Networks And Systems written by Radek Silhavy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-08 with Technology & Engineering categories.
The application of artificial intelligence in networks and systems is a rapidly evolving field that has the potential to transform a wide range of industries. The refereed proceedings in this book is from the Artificial Intelligence Application in Networks and Systems session of the Computer Science Online Conference 2023 (CSOC 2023), which was held online in April 2023. The section brings together experts from different fields to present their research and discuss the latest trends and challenges. One of the key themes in this section is the development of intelligent systems that can learn, adapt, and optimize their performance in real time. Researchers are exploring how AI algorithms can be used to create autonomous networks and systems that can make decisions without human intervention. Furthermore, this section highlights the use of AI in improving network performance and efficiency. Researchers are exploring how AI algorithms can be used to optimize network routing, reduce congestion, and improve the quality of service. These efforts can help organizations save costs and improve user experience.
Network Automation With Ai And Ml
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Author : Diego Rodrigues
language : es
Publisher: Diego Rodrigues
Release Date : 2024-11-20
Network Automation With Ai And Ml written by Diego Rodrigues and has been published by Diego Rodrigues this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-20 with Business & Economics categories.
Imagine a world where computer networks not only operate efficiently but also learn, adapt, and protect themselves from threats with minimal human involvement. Welcome to the revolutionary field of "Network Automation with AI and ML," where artificial intelligence and machine learning converge with the cutting edge of network technology. This book, written by renowned expert Diego Rodrigues, delves deep into the nearly limitless possibilities that emerge when intelligent algorithms govern our network systems. From optimizing performance to strengthening security, each page of this book is a step forward towards a future where networks are autonomous and self-optimizing. With a practical approach and full of case studies, Diego unveils how tools like Ansible, Nornir, Puppet, Chef, and SaltStack are being transformed by AI to create networks that not only respond but also anticipate needs and proactively defend against emerging threats. He discusses the current state of the technology and sketches a fascinating future where networks are sustainable and prepared for challenges we have yet to encounter. "Network Automation with AI and ML" is essential for IT professionals, network engineers, and anyone interested in understanding where the next generation of network automation is heading. By exploring advanced topics like Software-Defined Networking (SDN), machine learning algorithms, and predictive analytics from leading companies like Cisco, IBM, and Google, this book offers insights into creating smarter, more secure, and efficient networks. Dive into this comprehensive guide to discover how the integration of AI and ML with network automation tools can revolutionize the way we manage network infrastructures. Whether you are looking to enhance your technical skills or seeking to implement cutting-edge solutions in your organization, this book provides the knowledge and inspiration needed to shape the future of network technology. Grab your copy and get ready to be inspired and equipped to shape the future of network technology. TAGS: Python Java Linux Kali Linux HTML ASP.NET Ada Assembly Language BASIC Borland Delphi C C# C++ CSS Cobol Compilers DHTML Fortran General HTML Java JavaScript LISP PHP Pascal Perl Prolog RPG Ruby SQL Swift UML Elixir Haskell VBScript Visual Basic XHTML XML XSL Django Flask Ruby on Rails Angular React Vue.js Node.js Laravel Spring Hibernate .NET Core Express.js TensorFlow PyTorch Jupyter Notebook Keras Bootstrap Foundation jQuery SASS LESS Scala Groovy MATLAB R Objective-C Rust Go Kotlin TypeScript Elixir Dart SwiftUI Xamarin React Native NumPy Pandas SciPy Matplotlib Seaborn D3.js OpenCV NLTK PySpark BeautifulSoup Scikit-learn XGBoost CatBoost LightGBM FastAPI Celery Tornado Redis RabbitMQ Kubernetes Docker Jenkins Terraform Ansible Vagrant GitHub GitLab CircleCI Travis CI Linear Regression Logistic Regression Decision Trees Random Forests FastAPI AI ML K-Means Clustering Support Vector Tornado Machines Gradient Boosting Neural Networks LSTMs CNNs GANs ANDROID IOS MACOS WINDOWS Nmap Metasploit Framework Wireshark Aircrack-ng John the Ripper Burp Suite SQLmap Maltego Autopsy Volatility IDA Pro OllyDbg YARA Snort ClamAV iOS Netcat Tcpdump Foremost Cuckoo Sandbox Fierce HTTrack Kismet Hydra Nikto OpenVAS Nessus ZAP Radare2 Binwalk GDB OWASP Amass Dnsenum Dirbuster Wpscan Responder Setoolkit Searchsploit Recon-ng BeEF aws google cloud ibm azure databricks nvidia meta x Power BI IoT CI/CD Hadoop Spark Pandas NumPy Dask SQLAlchemy web scraping mysql big data science openai chatgpt Handler RunOnUiThread()Qiskit Q# Cassandra Bigtable VIRUS MALWARE docker kubernetes Kali Linux Nmap Metasploit Wireshark information security pen test cybersecurity Linux distributions ethical hacking vulnerability analysis system exploration wireless attacks web application security malware analysis social engineering Android iOS Social Engineering Toolkit SET computer science IT professionals cybersecurity careers cybersecurity expertise cybersecurity library cybersecurity training Linux operating systems cybersecurity tools ethical hacking tools security testing penetration test cycle security concepts mobile security cybersecurity fundamentals cybersecurity techniques skills cybersecurity industry global cybersecurity trends Kali Linux tools education innovation penetration test tools best practices global companies cybersecurity solutions IBM Google Microsoft AWS Cisco Oracle consulting cybersecurity framework network security courses cybersecurity tutorials Linux security challenges landscape cloud security threats compliance research technology React Native Flutter Ionic Xamarin HTML CSS JavaScript Java Kotlin Swift Objective-C Web Views Capacitor APIs REST GraphQL Firebase Redux Provider Angular Vue.js Bitrise GitHub Actions Material Design Cupertino Fastlane Appium Selenium Jest CodePush Firebase Expo Visual Studio C# .NET Azure Google Play App Store CodePush IoT AR VR GITHUB