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Issue title: AI-enabled Learning Techniques for Internet of Things Communications
Guest editors: Alireza Souri and Mu-Yen Chen
Article type: Research Article
Authors: Niu, Xina | Jiang, Jingjingb; *
Affiliations: [a] Changzhou Vocational Institute of Engineering, Changzhou 213164, Jiangsu, China. E-mail: 8000000326@czie.edu.cn | [b] School of Digital Technology, Dalian University of Science and Technology, Dalian 116052, Liaoning, China
Correspondence: [*] Corresponding author. E-mail: jiangjingjing@dlust.edu.cn.
Abstract: Multimedia is inconvenient to use, difficult to maintain, and redundant in data storage. In order to solve the above problems and apply cloud storage to the integration of university teaching resources, this paper designs a virtualized cloud storage platform for university multimedia classrooms. The platform has many advantages, such as reducing the initial investment in multimedia classrooms, simplifying management tasks, making maximum use of actual resources and easy access to resources. Experiments and analysis show the feasibility and effectiveness of the platform. Aiming at the problems of the single-node repair algorithm of the existing multimedia cloud storage system, the limited domain is large, the codec complexity is high, the disk I/O (Input/Output) cost is high, the storage overhead and the repair bandwidth are unbalanced, and a network coding-based approach is proposed. Multimedia cloud storage. System single node repair algorithm. The algorithm stores the grouped multimedia file data in groups in the system, and performs XOR (exclusive OR) on the data in the group on the GF(2) finite field. When some nodes fail, the new node only needs to be connected. Two to three non-faulty nodes in the same group can accurately repair the data in the failed node. Theoretical analysis and simulation results show that the algorithm can reduce the complexity and repair of the codec, and reduce the disk I/O overhead. In this case, the storage cost of the algorithm is consistent with the storage cost based on the minimum storage regeneration code algorithm, and the repair bandwidth cost is close to the minimum bandwidth regeneration code algorithm.
Keywords: Multimedia, cloud storage, network coding, single node repair, Internet
DOI: 10.3233/JHS-210661
Journal: Journal of High Speed Networks, vol. 27, no. 3, pp. 205-214, 2021
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