A heterogeneous multi-core architectural model for video scheduling for transcoding in clouds

Author:

Baital KalyanORCID,Chakrabarti Amlan

Publisher

Springer Science and Business Media LLC

Reference35 articles.

1. Li X et al (2019) Performance analysis and modeling of video transcoding using heterogeneous cloud services. IEEE Trans Parallel Distrib Syst 30(4):910–922

2. Li X et al (2016) CVSS: a cost-efficient and QoS-aware video streaming using cloud services. In: Proceeding of the 16th international symposium on cluster, cloud and grid computing (CCGrid). IEEE/ACM Cartagena, Colombia, pp 106–115

3. Baital K, Chakrabarti A (2019) An architectural approach for QoS aware video scheduling for transcoding in clouds. In: Proceeding of 5th international symposium on smart electrical system (iSES). IEEE, Rourkela, pp 164–167

4. Kim M, Cui Y, Han S, Lee H (2013) Towards efficient design and implementation of a hadoop-based distributed video transcoding system in cloud computing environment. Int J Multimed Ubiquitous Eng 8(2):213–224

5. Lin S, Zhang X, Yu Q, Qi H, Ma S (2013) Parallelizing video transcoding with load balancing on cloud computing. In: Proceedings of IEEE international symposium on circuits and system. Beijing, China, pp 2864–2867

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