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Effective Bandwidth Measurement for Dynamic Adaptive Streaming over HTTP

DASH시스템을 위한 유효 대역폭 측정 기법

  • Kim, Dong Hyun (School of Computer Science and Engineering, Pusan National University) ;
  • Jung, Jong Min (School of Computer Science and Engineering, Pusan National University) ;
  • Huh, Jun Hwan (School of Computer Science and Engineering, Pusan National University) ;
  • Kim, Jong Deok (School of Computer Science and Engineering, Pusan National University)
  • Received : 2016.08.18
  • Accepted : 2016.09.09
  • Published : 2017.01.31

Abstract

DASH (Dynamic Adaptive Streaming over HTTP) is an adaptive streaming technique that enables transmission of multimedia content when clients request the multimedia contents to server. In this system, to ensure the best quality of the content to satisfy users, it is necessary to precisely measure the residual bandwidth. However, the measured residual bandwidth by the DASH, which is not considering the transmission features of TCP, varies by the size of previous media segment, which makes it hard to ensure QoE to users. In this paper, we excluded the TCP Slow start range from measurement of residual bandwidth and suggested the new DASH bandwidth measuring method to decrease the error. Then, we realized the method in DASH system based on open source, and compared the existing measuring method. The new method showed that the accuracy of result has increased by 20%. Also, it could improve the QoE of users in terms of service quality and number of changes of segment quality.

DASH는 네트워크 상황에 따라 클라이언트가 서버에게 멀티미디어 콘텐츠를 요청하고 이를 이용하여 멀티미디어 콘텐츠를 전송하는 적응형 스트리밍 기술이다. 이러한 구조에서 멀티미디어 콘텐츠 사용자에게 최선의 품질을 보장하기 위해서는 정확한 가용 대역폭 측정이 필요하다. 그런데 TCP의 전송 특성을 고려하지 않는 DASH는 이전 미디어 세그먼트 크기에 따라 측정된 가용 대역폭이 다르고 때문에 사용자에게 QoE를 보장하기 어렵다. 본 논문은 TCP Slow start구간을 가용 대역폭 측정에서 배제하여 가용대역폭 측정 오류를 줄이는 새로운 dash대역폭 측정 방법을 제안한다. 제안 방법은 이전 세그먼트 크기에 따라 가용 대역폭 측정의 결과가 달라지는 문제를 해결할 수 있다. 우리가 제안하는 가용 대역폭 측정 방법을 오픈 소스 기반 DASH시스템에서 구현하여 기존 대역폭 측정 방법과 성능을 비교 평가하였다. 성능 평가 결과 제안 방법은 기존 대역폭 측정 방법에 비해 정확도가 20% 향상되었다. 또 평균 세그먼트 서비스 품질, 세그먼트 품질 변경 횟수 등의 측면에서 사용자 QoE가 개선됨을 확인하였다.

Keywords

References

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  1. Machine Learning based Bandwidth Prediction for Dynamic Adaptive Streaming over HTTP vol.10, pp.2, 2020, https://doi.org/10.14801/jaitc.2020.10.2.33