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Resource scheduling approach for multimedia cloud content management

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Abstract

With the development of multimedia application and services, the multimedia technology has already permeated each aspect of our life. Multimedia cloud is used for processing multimedia services. However due to huge data volume, high concurrency, strict real-time, resource scheduling for content dissemination in multimedia cloud still remain challenges. In order to increase the user satisfaction and decrease completion time of content dissemination, the resource scheduling for content dissemination in multimedia cloud is proposed in this paper. The multimedia jobs are clustered according to user expectation and job complexity. The job with highest priority will be executed first. Moreover, considered multimedia task types and the impact of stragglers, the multimedia task scheduling based on task types and node workload is presented, which is a time-efficient scheduling approach. The experiments are conducted and the experiment results show that the job clustering algorithm-based user expectation and job complexity in multimedia cloud has better user satisfaction and shorter completion time, while the multimedia task scheduling based on task types and node workload can reduce completion time and achieve load-balancing.

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Acknowledgements

The authors thank the editors and the anonymous reviewers for their helpful comments and suggestions. The work was supported by the National Natural Science Foundation (NSF) under Grants (Nos. 61672397, 61472294), the Jiangsu Key Laboratory of Image and Video Understanding for Social Safety (Nanjing University of Science and Technology), Grant No. 30916014107, Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education, Fuzhou University (No. 2016LSDMIS05), Program for the High-end Talents of Hubei Province. Any opinions, findings and conclusions are those of the authors and do not necessarily reflect the views of the above agencies.

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Authors and Affiliations

  1. Department of Computer Science, Wuhan University of Technology, Wuhan, 430063, People’s Republic of China

    Chunlin Li, Liye Zhu & Yanpei Liu

  2. Jiangsu Key Laboratory of Image and Video Understanding for Social Safety, Nanjing University of Science and Technology, Nanjing, 210094, People’s Republic of China

    Chunlin Li

  3. School of Management, Wuhan University of Technology, Wuhan, 430063, People’s Republic of China

    Youlong Luo

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  1. Chunlin Li
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  2. Liye Zhu
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Correspondence to Chunlin Li.

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Li, C., Zhu, L., Liu, Y. et al. Resource scheduling approach for multimedia cloud content management. J Supercomput 73, 5150–5172 (2017). https://doi.org/10.1007/s11227-017-2074-y

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  • DOI: https://doi.org/10.1007/s11227-017-2074-y

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