02419nas a2200253   4500000000100000000000100001008004100002260001200043653002400055653001400079653001800093653003200111653002000143100002000163700001700183700001900200700001600219245005600235856007900291300001000370490000600380520176500386022001402151       2021                            d  c09/202110aInteger Programming10aMPEG-DASH10aMotion Vector10aQuality Of Experience (QoE)10aVideo Streaming1 aShin-Hung Chang1 aMin-Lun Tsai1 aMeng-Huang Lee1 aJan-Ming Ho00aOptimal QoE Scheduling in MPEG-DASH Video Streaming  uhttps://www.ijimai.org/journal/sites/default/files/2021-08/ijimai6_7_7.pdf  a71-820 v63 aDASH is a popular technology for video streaming over the Internet. However, the quality of experience (QoE), a measure of humans’ perceived satisfaction of the quality of these streamed videos, is their subjective opinion, which is difficult to evaluate. Previous studies only considered network-based indices and focused on them to provide smooth video playback instead of improving the true QoE experienced by humans. In this study, we designed a series of click density experiments to verify whether different resolutions could affect the QoE for different video scenes. We observed that, in a single video segment, different scenes with the same resolution could affect the viewer’s QoE differently. It is true that the user’s satisfaction as a result of watching high-resolution video segments is always greater than that when watching low-resolution video segments of the same scenes. However, the most important observation is that low-resolution video segments yield higher viewing QoE gain in slow motion scenes than in fast motion scenes. Thus, the inclusion of more high-resolution segments in the fast motion scenes and more low-resolution segments in the slow motion scenes would be expected to maximize the user’s viewing QoE. In this study, to evaluate the user’s true experience, we convert the viewing QoE into a satisfaction quality score, termed the Q-score, for scenes with different resolutions in each video segment. Additionally, we developed an optimal segment assignment (OSA) algorithm for Q-score optimization in environments characterized by a constrained network bandwidth. Our experimental results show that application of the OSA algorithm to the playback schedule significantly improved users’ viewing satisfaction.  a1989-1660