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IAR: An Interaction-Aware Approach to Post-Seek Recovery in Adaptive HLS Streaming
arXiv eess.IV0 views
arXiv:2610.33120v1 Announce Type: new Abstract: After an unbuffered seek, an adaptive bitrate (ABR) player has little forward buffer at the new position, while its controller may retain a bandwidth estimate from earlier downloads. An expensive first request can delay resumption; later requests may interrupt playback while the buffer rebuilds. We introduce Interaction-Aware Recovery (IAR), a temporary layer around the hls.js ABR controller. After an unbuffered seek, IAR discounts the inherited estimate ({\gamma}=0.15) to set a representation ceiling. Normal adaptation continues below it until 8 s of forward buffer has been rebuilt. In a 200-run paired study spanning four network profiles, ten seek positions, and five strategies, a conservative first request reduced resume delay by a paired median of 2.008 s relative to standard hls.js. Keeping a low ceiling through recovery reduced later interruption under stronger degradation but lowered early presented bitrate. IAR and Fixed-Low-Recovery both used L0 in this campaign, so the results did not show an additional benefit from deriving the ceiling from inherited bandwidth. In 60 additional runs under a fixed Moderate profile, we reset the estimator to six controlled scalar priors. IAR's ceiling changed from L0 to L1 and L2 at the predicted thresholds. Resume and recovery times increased at those transitions; presented bitrate varied non-monotonically and was highest at L2. No stalls occurred. These reset-created priors do not reproduce complete, naturally evolved exponentially weighted moving average (EWMA) histories. The results show the benefits and presented-quality costs of conservative post-seek recovery, without establishing an advantage for a history-derived ceiling over a fixed low ceiling.
Source:https://arxiv.org/abs/2610.33120PreviousSimulated transcranial ultrasound of human language cortex: verifying heard speech needs far less data and signal than decoding itNextSpectrally optimized implicit neural representations mitigate acquisition-related image quality trade-offs in intracranial 4D Flow MRI
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