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Turning Video Resource Management into Cloud Computing

Author

Listed:
  • Weili Kou

    (School of Computer and Information, Southwest Forestry University, Kunming 650224, China)

  • Hui Li

    (School of Computer and Information, Southwest Forestry University, Kunming 650224, China)

  • Kailai Zhou

    (School of Computer and Information, Southwest Forestry University, Kunming 650224, China)

Abstract

Big data makes cloud computing more and more popular in various fields. Video resources are very useful and important to education, security monitoring, and so on. However, issues of their huge volumes, complex data types, inefficient processing performance, weak security, and long times for loading pose challenges in video resource management. The Hadoop Distributed File System (HDFS) is an open-source framework, which can provide cloud-based platforms and presents an opportunity for solving these problems. This paper presents video resource management architecture based on HDFS to provide a uniform framework and a five-layer model for standardizing the current various algorithms and applications. The architecture, basic model, and key algorithms are designed for turning video resources into a cloud computing environment. The design was tested by establishing a simulation system prototype.

Suggested Citation

  • Weili Kou & Hui Li & Kailai Zhou, 2016. "Turning Video Resource Management into Cloud Computing," Future Internet, MDPI, vol. 8(3), pages 1-10, July.
    • Handle: RePEc:gam:jftint:v:8:y:2016:i:3:p:35-:d:74414
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    Cited by:

    1. Carmen De-Pablos-Heredero, 2017. "Future Intelligent Systems and Networks," Future Internet, MDPI, vol. 9(3), pages 1-2, September.

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