Content Delivery Networks Using Artificial Intelligence and Internet of Things

Tanusree Chatterjee, PhD is an Associate Professor at the Future Institute of Technology, a unit of the Techno India Group. She has published more than 18 papers in international journals and conference proceedings, co-authored two books, and holds one patent. Her current research interests include artificial intelligence, machine learning, and the Internet of Things. Rajib Banerjee, PhD is an Associate Professor in the School of Computer Science at the University of Petroleum and Energy Studies with more than 22 years of experience. He has published many research articles in journals and conferences, as well as several patents. His research interests include wireless sensor networks, wireless multimedia sensor networks, and low-power multimedia processing. Souvik Ganguli, PhD is an Assistant Professor at the Thapar Institute of Engineering and Technology, Patiala, India. He has published more than 50 papers in journals, conferences, and book chapters and holds 15 patents. His research interests include IoT-based control, delta operator modeling, and robust identification.

• Preface xv1 Introduction to AIIoT and CDNs 1Priyanka Pramod Pawar, R. Kannan, R. Anand, Deepak Kumar, K. Arunprasath, A. Bhuvanesh and Tanusree Chatterjee1.1 AIoT Explained: The Convergence of AI and IoT 21.2 The Interrelationship between AIoT and CDN 51.3 Advantages of AIoT in Content Distribution 71.4 Major Challenges in the Integration of AIoT and CDN 101.5 Optimizing Latency and Network Efficiency 131.6 Real-Time Data Processing and Analytics 161.7 Scalability and Adaptability of AIoT-CDN Systems 181.8 AIoT and CDN Networks Security and Privacy 201.9 Future Trends in AIoT and CDN Technologies 221.10 Conclusion: Toward Smarter, Faster Digital Infrastructures 262 Predictive Caching Strategies Using Machine Learning for Seamless Content Access 31Jagendra Singh, Monika Dandotiya, Shivani Agarwal, Kannan Srinivasan, Rahul Jadon and Guman Singh Chauhan2.1 Introduction 322.2 Related Work 332.3 Methodology 352.4 Result and Discussion 432.5 Conclusion 493 Artificial Intelligence in Context Delivery 53Vaishnavi and Navneet Kumar3.1 Introduction 543.2 Benefits of Machine Learning for Caching 583.3 Understanding Advanced CDN Architecture 593.4 Mechanisms Behind Context-Aware AI Systems 613.5 Applications of AI in Context Delivery 613.6 Benefits of AI in Context Delivery 623.7 Challenges in Context Delivery (CD) 633.8 Summary and Discussion 633.9 Conclusion 664 Monetizing Cyberliterature through AI-Enhanced Networks in English Education System 69Muthmainnah Muthmainnah, Luis Cardoso, Ahmad Al Yakin, Khristianto Khristianto, Widya Nirmalawati and Titik Wahyuningsih4.1 Introduction 704.2 Literature Review 724.3 Methodology 804.4 Findings and Discussions 834.5 Discussion 904.6 Conclusions 945 Understanding AI with IoT, Real-Time Applications in Image Dehazing 101Malladi Sunder Rao and Dilip Kumar5.1 Introduction 1015.2 The Integration of AI and IoT 1035.3 Introduction to Image Dehazing 1055.4 The Dehazing Process Model 1085.5 General Process of Dehazing or Haze Removal Model 1095.6 Datasets for the Dehazing Process 1125.7 Network Section 1125.8 Applications of Image Dehazing in AI IoT 1135.9 Case Studies 1145.10 Features of the PYNQ-Z2 Board 1155.11 Advantages of Integrating AI with IoT 1165.12 Application of the PYNQ-Z2 Board 1175.13 Loss Function 1185.14 Conclusion 1206 Data-Driven Optimization of Content Distribution: Leveraging AI for Personalization and Scalability 123Jagendra Singh, Namita Nath, Lucky Gupta, Swapna Narla, Sreekar Peddi and Dharma Teja Valivarthi6.1 Introduction 1246.2 Problem Statement 125viii Contents6.3 Literature Review 1266.4 Methodology 1286.5 Result and Discussion 1366.6 Conclusion 1437 Generative AI and Content Delivery Networks: Revolutionizing Content Delivery and Learning Management with AI-Driven Innovation 147Kamini, Sanjay Kumar Sonker, Ashish Kumar, Manoj Kumar, Prem Prakash Agrawal and Ramendra Singh7.1 Introduction 1487.2 Problem Statement 1497.3 Literature Review 1507.4 Methodology 1517.5 Result and Discussion 1617.6 Conclusion 1688 Adaptive Video Streaming and Content Personalization Using Generative Models 171Afreen Fatima Mohammed, Vijayalakshmi Chintamaneni, Jagendra Singh, Kalyan Gattupalli, Venkata Surya Bhavana Harish Gollavilli and Surendar Rama Sitaraman8.1 Introduction 1728.2 Problem Statement 1738.3 Literature Review 1748.4 Methodology 1758.5 Result and Discussion 1848.6 Conclusion 1909 Data Analytics and Real-Time Decision Making in Water Quality Prediction 193Kajal Kumari, Sudip Kumar Sahana and Debjani Mustafi9.1 Introduction 1949.2 Related Work 1959.3 Dataset Description 1969.4 Methodology of Proposed Model 1989.5 Experimental Setup 2039.6 Results and Discussion 2049.7 Conclusion 20810 Enhancing E-Commerce Security: A Framework of Integrated Vulnerability Assessment and Data Privacy Protection 213Aftab Ara10.1 Introduction 21410.2 Literature Review 21410.3 Findings 22010.4 Conceptual Framework for E-Commerce Security 222x Contents10.5 Discussions 22410.6 Implications 22510.7 Conclusion 22611 Enhancing Content Delivery Networks with Generative AI: Strategies, Applications, and Future Directions 231Subhranil Das, Rashmi Kumari and Raghwendra Kishore Singh11.1 Introduction 23211.2 Fundamentals of Generative AI Techniques for CDNs 23411.3 Intelligent Caching Strategies for CDNs with Generative AI 24411.4 Ethical and Security Concerns in Generative AI for CDNs 25011.5 Conclusion and Future Scope 25312 An IoT-Enabled Indoor Tracking Base System (IITBS) for Human Activities Identification 259Pulakesh Roy, Sushmita Chaudhari, Surabhi Solanki, Rajib Banerjee and Arindam Biswas12.1 Introduction 26012.2 Literature Review 26112.3 Structure Design 26512.4 Outcomes and Performance 27012.5 Conclusion 27513 AI and IoT-Driven Machine Learning in CDNs: Advancing Diagnostic Precision in Breast Cancer Screening 279Shubhranshu Gorai, Saibal Majumder, Ritik Maity, Mehuli Lahiri, Sovan Bhattacharya, Dola Sinha, Suchandra Banerjee and Chandan Bandyopadhyay13.1 Introduction 28013.2 Dataset Description 28313.3 Methodology 28613.4 Machine Learning Models 28813.5 Performance Metrics 28913.6 Results and Discussions 29113.7 Conclusion 30314 Rethinking Cybersocialization in Posthumanist: An Evolution of University Curriculum Based on AIIoT Automation 307Ahmad Al Yakin, Ali Said Al Matari, Abd. Ghofur, Muthmainnah Muthmainnah, Ahmed J. Obaid and Souvik Ganguli14.1 Introduction 30814.2 Literature Review 31014.3 Methodology 32014.4 Findings and Discussion 32114.5 Discussion 32814.6 Conclusions 33315 Future Trends and Innovation Education 7.0 by Adopting AIIoT Networks 341Besse Darmawati, Ade Mulyanah, Adri Adri, Ratnawati Ratnawati, Resti Nurfaidah, Muthmainnah Muthmainnah and Souvik Ganguli15.1 Introduction 34215.2 Literature Review 34415.3 Research Methodology 35415.4 Findings and Discussion 35615.5 Conclusion 365References 366Index 375