ABR Quality Monitoring: State of the Art

James Welch

With the move to increasingly complex adaptive bitrate technology for video transport delivery comes a corresponding increase in quality assurance complexity. Video service providers require more information than only that some number of viewers are unsatisfied with their viewing experience. More proactive warnings of deteriorating service and the descriptions of specific impairments, for example, are needed for rapid corrective actions. This paper describes both common industry approaches to quality monitoring for Hypertext Transfer Protocol (HTTP) Live Streaming (HLS) and dynamic adaptive streaming over HTTP (DASH) delivery methods as well as video content quality evaluation leveraging mean opinion score (MOS), bits per pixel, and other metrics aimed at evaluating if viewers have a satisfactory viewing experience. A comprehensive set of metrics including both those recommended by standards and trade groups as well as key supplemental metrics for both end user viewing and transport system analysis is discussed along with the tradeoffs in measurement implementation techniques gained from significant deployments for some past entertainment events. Recommendations on the selection of a mix of reactive and proactive metrics are provided as derived from synthetic clients, passive agent technologies, and virtual swarming agents. Both transport and content quality metrics are critical in assessing viewers’ experience and pinpointing impairment causes and viewer losses.

Print ISSN
Electronic ISSN
2160-2492
Published
2019-05
Content type
Original Research
Keywords
Adaptive bitrate (ABR) monitoring, ABR streaming quality, asset accessibility, asset availability, caching, encoder quality, end-to-end monitoring, guided troubleshooting, hypertext transfer protocol (HTTP) streaming, intracontent delivery network (intra-CDN), origin server, passive monitoring, proactive monitoring, quality of Experience, quality of Service (QOS) stream-monitoring metrics, stream publishing, synthetic client, transcoder evaluation, veriStream, video-monitoring automation
DOI
10.5594/JMI.2019.2901209