Squash: low latency multi-path video streaming using multi-bitrate encoding
Notice bibliographique
Résumé
The demand for low latency video streaming has dramatically increased as live video streaming applications, such as Twitch and Youtube Live, are becoming more popular. According to the 2021 Bitmovin video developer report, the biggest challenge that video developers are experiencing today is providing low latency video streaming. One of the most common on-site live streaming methods is using a wireless LTE network. There have been many approaches for characterizing wireless links and accurately measuring available bandwidth to provide low latency streaming over a wireless LTE network link. However, even with fine-grained bandwidth estimation, video streaming on a single LTE link is still susceptible to unexpected network delay from a sudden drop in available bandwidth or temporal disconnection. \n \nPeople can utilize multiple wireless LTE links to overcome the limitations of using a single LTE link for low latency video streaming. Using multiple links can enhance video quality through increased bandwidth and resilience. However, multi-homed low latency video streaming protocols may achieve lower video quality than single-homed protocols when a frame is split and sent over more than one link. Suppose one of the links becomes congested or gets disconnected. In that case, the part of the frame sent on stable links must wait until the packets sent on the problematic link are re-transmitted through another link. Re-transmission requires at least one extra round trip time. A video player may skip the late frame or serve only the received part of the frame due to the re-transmission delay. Ferlin et al. suggest using Forward Error Correction (FEC) on Multipath TCP (MPTCP) to reduce re-transmission delay. However, FEC is not helpful in the event of a significant bandwidth drop. If the sender does not use sufficient redundancy to handle a significant bandwidth drop, the receiver will not receive enough blocks to decode the video data. FEC requires using a large portion of the network bandwidth for redundancy to handle significant bandwidth drops even when the links are stable. \n \nIn this thesis, I present Squash, a low latency video transport protocol that encodes each frame at multiple bitrates and sends them across different links to minimize video stream disruption in the event of unexpected bandwidth drops. The encoder encodes a frame into multiple different bitrates, which are high-bitrate and low-bitrate. When a high- bitrate frame cannot arrive on time due to congestion from an unexpected drop in available bandwidth, the low-bitrate frame is used to replace the missing frame. This is because the low-bitrate frame is smaller and is sent on the links that are disjoint from those used by the high-bitrate frame. To the best of my knowledge, Squash is the first architecture that uses multi-bitrate frames to increase resilience against unexpected bandwidth drops in low latency video streaming over multiple wireless LTE links. In emulated wireless LTE network environment using Mahimahi network traces, the average SSIM of the video streamed on Squash is 13 – 58% higher than that streamed on the baseline protocol, which is designed in the same manner as Squash except that it employs single-frame encoding.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».