Augmented Reality as a Telemedicine Platform for Remote Procedural Training.
Nearly three-fourths of the world's mobile data traffic will be video in the next 5 years. Video is one of the most demanding services in terms of network efficiency, reliability, and quality. In this work, we present a comparative performance evaluation of three different video streaming protocols, namely MPEG-DASH, RTSP, and RTMP for both on-demand and live video streaming over 4G and Wi-Fi (under different network conditions) in terms of Quality of user Experience (QoE). QoE measurements have been done (i) applying the recently standardized ITU-T Rec P-1201.1, which specifies the model algorithm for non-intrusive monitoring of video quality of IP-based video services based on packet header information for the lower resolution application area, and (ii) an extended non-standardized parametric model for comparative purposes. Results suggest that RTSP is more efficient than MPEG DASH for starting the video playback, but at the expense of decreasing QoE due to packet losses. We have also detected that PLR has a bigger influence over re-buffering events than end-to-end delay both in 4G/LTE and Wi-Fi, and that a slightly best quality is achieved by using QPSK at 20 MHz in 4G/LTE. QoE is noticeably higher with MPEG DASH than that attained by using RTSP, but slightly worse than that obtained with RTMP. Finally, our findings suggest that the use of parametric models for video QoE evaluation should be carefully review in terms of the weight that packet losses should have when streaming protocols based on reliable transport protocols (e.g., TCP) are used.