Abstract
Dynamic adaptive streaming over Hypertext Transfer Protocol (HTTP) is an advanced technology in video streaming to deal with the uncertainty of network states. However, this technology has one drawback as the network states frequently and continuously change. The quality of a video streaming fluctuates along with the network changes, and it might reduce the quality of service. In recent years, many researchers have proposed several adaptive streaming algorithms to reduce such changes. However, these algorithms only consider the current state of a network. Thus, these algorithms might result in inaccurate estimates of a video quality in the near term. Therefore, in this paper, we propose a method using fuzzy logic and a mathematics moving average technique, in order to reduce mobile video quality fluctuation in Dynamic Adaptive Streaming over HTTP (DASH). First, we calculate the moving average of the bandwidth and buffer values for a given period. On the basis of differences between real and average values, we propose a fuzzy logic system to deduce the value of the video quality representation for the next request. In addition, we use the entropy rate of a bandwidth measurement sequence to measure the predictable/stabilization of our method. The experiment results show that our proposed method reduces video quality fluctuation as well as improves 40% of bandwidth utilization compared to existing methods.
Highlights
Users recently have had access to increased network bandwidth such as 5G technology
1 GetListOfResolution() in Media Presentation Description (MPD) file; 2 k = a natural number //trace-back step; 3 while not end of video streaming do Calculate moving average of buffer and bandwidth value by using Equations (2)–(4); Fuzzification using Equations (5) and (6); Fuzzy Inference using Table 1; ouput = Defuzzification using Equation (7); Ei = CalcualteEntropyRate() using Equation (10); Eaverage = AverageEntropyRate() (using (∑ j=0,i Ej )/i); if Ei > Eaverage k = k − k/2; else k = k + k/2; end for Resol in ResolutionList do if segment width at Equation (8) > width of Resol representation is Resol; break; end end
Our approach entropy rate on the left and right sides of Table 2 are different since we tested in two scenarios, which are real network tests to compare with nonlinear and NS3 test to compare with FDASH
Summary
Users recently have had access to increased network bandwidth such as 5G technology. On the one hand, users have many advantages in streaming services. It brings the user to the huge gap of fluctuation between a low and high throughput This problem degrades the quality of mobile services such as video streaming because the streaming is sensitive to network changes. The problem has not been resolved thoroughly because the adaptive streaming frequently changes bitrates if network metric values such as bandwidth continuously change from low to high. Researchers have invested the problem and proposed many adaptive algorithms to improve network utilization and reduce the changes. An adaptive algorithm does select representations of video streaming that match to the current network state. As addressed in [8], the problem is challenging because adaptive streaming-based always has an inevitable mismatch between the actual network throughput and the selected video bitrate. We conclude our work with the future work of the research
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