Optimization of User-Specific Video Chunk Streaming Using Softmax Classification 


Vol. 43,  No. 12, pp. 2107-2113, Dec.  2018
10.7840/kics.2018.43.12.2107


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  Abstract

As the demand of OTT service and online streaming service such as Youtube and neflix increases, many techniques for ensuring QoE(Quality of Experience) have been studied. But existing studies have a limit in that they did not consider parameters in QoS. That is users. This means that there is an upper limit to the QoE improvement of existing techniques. In this paper, we propose a solution for address this kinds of problem using UAS(User-based Adaptive Streaming). The proposed method analyzes the user`s video watching patterns based on the Softmax algorithm. Then, according to the anlysis result, the priority of receiving each of the video chunks is adjusted. Finally, the UAS technique aims to make the best of QoE through optimized streaming loading. And you can know that the designed technique shows that the waiting time felt by the user is significantly lower than the existing streaming techniques through the experimental results.

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  Cite this article

[IEEE Style]

K. Kim and J. Kim, "Optimization of User-Specific Video Chunk Streaming Using Softmax Classification," The Journal of Korean Institute of Communications and Information Sciences, vol. 43, no. 12, pp. 2107-2113, 2018. DOI: 10.7840/kics.2018.43.12.2107.

[ACM Style]

Kyeongseon Kim and Joongheon Kim. 2018. Optimization of User-Specific Video Chunk Streaming Using Softmax Classification. The Journal of Korean Institute of Communications and Information Sciences, 43, 12, (2018), 2107-2113. DOI: 10.7840/kics.2018.43.12.2107.

[KICS Style]

Kyeongseon Kim and Joongheon Kim, "Optimization of User-Specific Video Chunk Streaming Using Softmax Classification," The Journal of Korean Institute of Communications and Information Sciences, vol. 43, no. 12, pp. 2107-2113, 12. 2018. (https://doi.org/10.7840/kics.2018.43.12.2107)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880