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Cloud Computing Based Digital Media Content Distribution Technology.
- Source :
- Procedia Computer Science; 2024, Vol. 247, p461-468, 8p
- Publication Year :
- 2024
-
Abstract
- The rapid development of digital media content and the increasing demand of users for high-quality content have made digital media content distribution technology more and more important in practical applications. Cloud computing, as an infrastructure, has the advantages of flexible scalability and high quality for storage, management and distribution of digital media content. However, more in-depth research is needed to understand the impact of content distribution strategies under different network environments and media types. In this paper, based on the cloud computing platform, a series of comparative experiments were designed to evaluate the performance of cloud computing based digital media content distribution technology from different aspects. Factors considered in this paper included different network types, bandwidth, latency, packet loss rate, media types (video, audio, image) and distribution strategies. The experimental data is collected and analyzed, and the key indicators such as download time and playback success rate are evaluated. After analyzing the experimental results, we find that the performance of digital media content distribution is significantly affected by different network environments and media types. Cloud computing based content distribution strategies have been proved to achieve the effect of fast download and high success playback rate. The response time of cloud based distribution strategies is up to 4.7 seconds, and the bandwidth utilization rate reaches 89%, and the minimum latency is 104 ms. Under the same conditions, the performance of cloud computing is generally better than that of Content Delivery Network (CDN) and Peer-to-Peer (P2P). This study is a comprehensive experimental study of cloud computing based digital media content distribution technology. It has in-depth understanding of the performance of network environment, media types and distribution strategies. These research results have important reference and guidance to optimize digital media content distribution technology and improve the user experience. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 18770509
- Volume :
- 247
- Database :
- Supplemental Index
- Journal :
- Procedia Computer Science
- Publication Type :
- Academic Journal
- Accession number :
- 180928919
- Full Text :
- https://doi.org/10.1016/j.procs.2024.10.055