Enhancing Video Streaming with AI, Cloud, and Edge Technologies Optimization Techniques and Frameworks /
This book explores how artificial intelligence, cloud computing, and edge technologies are transforming video streaming systems. It delves into AI-driven adaptive bitrate streaming, predictive resource allocation, and federated learning for personalized recommendations. The integration of cloud and...
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| Main Authors: | , |
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| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2025.
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| Edition: | 1st ed. 2025. |
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| Online Access: | https://doi.org/10.1007/978-3-031-84651-9 |
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| 100 | 1 | |a Darwich, Mahmoud. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Enhancing Video Streaming with AI, Cloud, and Edge Technologies |h [electronic resource] : |b Optimization Techniques and Frameworks / |c by Mahmoud Darwich, Magdy Bayoumi. |
| 250 | |a 1st ed. 2025. | ||
| 264 | 1 | |a Cham : |b Springer Nature Switzerland : |b Imprint: Springer, |c 2025. | |
| 300 | |a XXIII, 338 p. 107 illus., 106 illus. in color. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 341 | 0 | |b Table of contents navigation |2 onix | |
| 341 | 0 | |b Single logical reading order |2 onix | |
| 341 | 0 | |b Short alternative textual descriptions |2 onix | |
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| 341 | 0 | |b Next / Previous structural navigation |2 onix | |
| 341 | 0 | |b All non-decorative content supports reading without sight |2 onix | |
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| 505 | 0 | |a Part I Foundations and Challenges in Video Streaming -- Chapter 1 Introduction to Video Streaming Systems and Challenges -- Part II AI-Driven Approaches for Video Streaming -- Chapter 2 AI-Driven Video Quality Assessment and Enhancement Techniques -- Chapter 3 Federated Learning for Scalable Video Streaming -- Chapter 4 Deep Learning for Adaptive Video Quality -- Part III Cloud and Edge Computing in Video Streaming -- Chapter 5 Cloud-Enhanced Video Streaming: Storage and Resource Management -- Chapter 6 Edge Computing for Low-Latency Video Streaming -- Chapter 7 Swarm Intelligence for Efficient Video Data Distribution in Edge Networks -- Part IV Emerging Technologies in Video Streaming -- Chapter 8 Blockchain-Enhanced Distributed Storage for Cloud-Based Video Streaming -- Chapter 9 AI-Driven Resource Allocation and Optimization in Video Streaming -- Part V Practical Implementations and Future Trends -- Chapter 10 Case Studies and Real-World Implementations of AI, Cloud, and Edge in Video Streaming -- Chapter 11 Conclusion and Future Directions for Video Streaming Enhancements. | |
| 520 | |a This book explores how artificial intelligence, cloud computing, and edge technologies are transforming video streaming systems. It delves into AI-driven adaptive bitrate streaming, predictive resource allocation, and federated learning for personalized recommendations. The integration of cloud and edge computing is highlighted as a solution for scalability and low-latency streaming, addressing challenges like bandwidth optimization, cost-efficiency, and Quality of Experience (QoE). The book offers actionable insights into emerging technologies like 5G, quantum computing, and blockchain. It features case studies and real-world implementations, making it an essential resource for researchers, industry professionals, and students. Bridging theory and practice, the book provides a comprehensive guide to building the next generation of efficient and scalable video streaming infrastructures. | ||
| 532 | 8 | |a Accessibility summary: This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. | |
| 532 | 8 | |a No reading system accessibility options actively disabled | |
| 532 | 8 | |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com | |
| 650 | 0 | |a Multimedia systems. | |
| 650 | 0 | |a Cloud Computing. | |
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 1 | 4 | |a Multimedia Information Systems. |
| 650 | 2 | 4 | |a Cloud Computing. |
| 650 | 2 | 4 | |a Artificial Intelligence. |
| 700 | 1 | |a Bayoumi, Magdy. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
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| 856 | 4 | 0 | |u https://doi.org/10.1007/978-3-031-84651-9 |
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| 950 | |a Computer Science (SpringerNature-11645) | ||
| 950 | |a Computer Science (R0) (SpringerNature-43710) | ||
| 950 | |a Focus Bundle Software and Systems (SpringerNature-85409) | ||