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  • Enhancing Video Streaming with AI, Cloud, and Edge Technologies: Optimization Techniques and Frameworks

    Enhancing Video Streaming with AI, Cloud, and Edge Technologies by Darwich, Mahmoud; Bayoumi, Magdy;

    Optimization Techniques and Frameworks

      • GET 20% OFF

      • The discount is only available for 'Alert of Favourite Topics' newsletter recipients.
      • Publisher's listprice EUR 213.99
      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

        90 774 Ft (86 451 Ft + 5% VAT)
      • Discount 20% (cc. 18 155 Ft off)
      • Discounted price 72 619 Ft (69 161 Ft + 5% VAT)

    90 774 Ft

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    Availability

    Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
    Not in stock at Prospero.

    Why don't you give exact delivery time?

    Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.

    Product details:

    • Publisher Springer
    • Date of Publication 28 March 2025
    • Number of Volumes 1 pieces, Book

    • ISBN 9783031846502
    • Binding Hardback
    • No. of pages338 pages
    • Size 235x155 mm
    • Language English
    • Illustrations 1 Illustrations, black & white; 106 Illustrations, color
    • 682

    Categories

    Short description:

    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.

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    Long description:

    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.

    More

    Table of Contents:

    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.

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