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Turning Video Resource Management into Cloud Computing

School of Computer and Information, Southwest Forestry University, Kunming 650224, China
Author to whom correspondence should be addressed.
Academic Editor: Dino Giuli
Future Internet 2016, 8(3), 35;
Received: 13 December 2015 / Revised: 27 May 2016 / Accepted: 12 July 2016 / Published: 21 July 2016
(This article belongs to the Special Issue Future Intelligent Systems and Networks)
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. View Full-Text
Keywords: video resources; big data; cloud computing; HDFS video resources; big data; cloud computing; HDFS
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MDPI and ACS Style

Kou, W.; Li, H.; Zhou, K. Turning Video Resource Management into Cloud Computing. Future Internet 2016, 8, 35.

AMA Style

Kou W, Li H, Zhou K. Turning Video Resource Management into Cloud Computing. Future Internet. 2016; 8(3):35.

Chicago/Turabian Style

Kou, Weili, Hui Li, and Kailai Zhou. 2016. "Turning Video Resource Management into Cloud Computing" Future Internet 8, no. 3: 35.

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