Turning Video Resource Management into Cloud Computing

Weili Kou, Hui Li and Kailai Zhou
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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

Future Internet, 2016, vol. 8, issue 3, 1-10

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.

Keywords: video resources; big data; cloud computing; HDFS (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2016
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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