QoE-enhanced adaptation algorithm over DASH for multimedia streaming

In dynamic adaptive streaming over HTTP (DASH), a client consecutively estimates the available network bandwidth and decides the transmission rate for the forthcoming video chunks to be downloaded. Even though several enhancements to DASH have been reported in the literature, they do not well-investigate the current buffer status to cope with fluctuating network conditions and thus do not achieve seamless video streaming. In this paper, we propose a novel rate adaptation algorithm called quality of experience (QoE)-enhanced adaptation algorithm over DASH (QAAD), which preserves the minimum buffer length to avoid interruption and minimizes the video quality changes during the playback. We implemented a DASH testbed and conducted extensive experiments. Experimental results demonstrate that under fluctuating network conditions, QAAD provides seamless streaming with stabilized video quality while the previous buffer-aware algorithm (i.e., QoE-aware DASH) frequently changes the video quality and undergoes the interruption.