Optimizing Video Streaming Protocols for Content Delivery Networks (CDN)

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@article{1706235,
      author = {Narrain Prithvi Dharuman, Rakesh Jena, Saketh Reddy Cheruku, Niharika Singh, Prof. (Dr) Punit Goel; Om Goel},
      title = {Optimizing Video Streaming Protocols for Content Delivery Networks (CDN)},
      journal = {Iconic Research And Engineering Journals},
      year = {2024},
      volume = {8},
      number = {3},
      pages = {765-784},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1706235.pdf},
      abstract = {The increasing demand for high-quality video streaming has significantly challenged traditional content delivery networks (CDNs) to optimize their protocols for efficient content distribution. This paper explores the optimization of video streaming protocols within CDN architectures, focusing on enhancing delivery speed, reducing latency, and improving user experience. We analyze various streaming protocols, such as HTTP Live Streaming (HLS) and Dynamic Adaptive Streaming over HTTP (DASH), and their roles in managing network congestion and adapting to fluctuating bandwidth conditions. Furthermore, we investigate the integration of edge computing and caching strategies to minimize latency and improve the availability of content. By employing machine learning algorithms, CDNs can predict traffic patterns and user behavior, allowing for proactive adjustments in streaming protocols to optimize resource allocation and enhance overall performance. This study also highlights the importance of Quality of Experience (QoE) metrics in evaluating the effectiveness of optimized protocols, ensuring that end-users receive seamless streaming experiences. Through comprehensive simulations and case studies, we demonstrate the potential of advanced optimization techniques in addressing the complexities of video streaming in CDN environments. The findings of this research contribute to the ongoing efforts to develop robust and adaptive streaming solutions that meet the ever-growing demands of consumers while maintaining cost-effectiveness for service providers. Ultimately, this work serves as a foundation for future research in the optimization of video streaming protocols, paving the way for more efficient and reliable content delivery in an increasingly digital world.},
      keywords = {Optimizing, video streaming protocols, content delivery networks, CDN, HTTP Live Streaming, Dynamic Adaptive Streaming, edge computing, caching strategies, machine learning, Quality of Experience, resource allocation, performance enhancement.},
      month = {September},
  }