Confused, timid, and unstable: picking a video streaming rate is hard

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A Survey on Quality of Experience of HTTP Adaptive Streaming (2015, neutral): “Depending on the specific implementation of the HAS control algorithm, particularly on its aggressiveness, less than the fair share of the resources is used [144].”
Probe and Adapt: Rate Adaptation for HTTP Video Streaming At Scale (2013, background): “Our claim is based on a number of experimental studies of commercial HAS players [2], [11], [14].”
A buffer-based approach to rate adaptation (2014, background): “In the presence of competing TCP ﬂows, the ON-OFF pattern can trigger a bad interaction between TCP and the ABR algo-rithm, causing a further underestimate of capacity and a downward spiral in video quality [9].”
Oboe: auto-tuning video ABR algorithms to network conditions (2018, background): “Internet video forms a major fraction of Internet traffic today [13], and delivering high quality of experience (QoE) is critical since it correlates with user engagement and revenue [6, 23, 31].”
Neural Adaptive Video Streaming with Pensieve (2017, background): “However, many of these goals are inherently conflicting [3, 18, 21].”