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JBE, vol. 23, no. 1, pp.104-114, January, 2018

DOI: https://doi.org/10.5909/JBE.2018.23.1.104

A Video-Quality Control Scheme using ANFIS Architecture in a DASH Environment

Ye-Seul Son, Hyun-Jun Kim, and Joon-Tae Kim

C.A E-mail: jtkim@konkuk.ac.kr

Abstract:

Recently, as HTTP-based video streaming traffic continues to increase, Dynamic Adaptive Streaming over HTTP(DASH), which is one of the HTTP-based adaptive streaming(HAS) technologies, is receiving attention. Accordingly, many video quality control techniques have been proposed to provide a high quality of experience(QoE) to clients in a DASH environment. In this paper, we propose a new quality control method using ANFIS(Adaptive Network based Fuzzy Inference System) which is one of the neuro-fuzzy system structure. By using ANFIS, the proposed scheme can find fuzzy parameters that selects the appropriate segment bitrate for clients. Also, considering the characteristic of VBR video, the next segment download time can be more accurately predicted using the actual size of the segment. And, by using this, it adjusts video quality appropriately in the time-varying network. In the simulation using NS-3, we show that the proposed scheme shows higher average segment bitrate and lower number of bitrate-switching than the existing methods and provides improved QoE to the clients.

 



Keyword: MPEG-DASH, Adaptive bitrate streaming, Video-Quality Control, Neuro-Fuzzy System, ANFIS

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