AutoRec: Accelerating Loss Recovery for Live Streaming in a Multi-Supplier Market

TL;DR

AutoRec is a novel loss recovery mechanism for live streaming that reduces latency and improves quality of experience by adaptively managing retransmissions without requiring client modifications.

Contribution

The paper introduces AutoRec, an adaptive loss recovery system for live streaming that operates without client changes and effectively reduces recovery latency in dynamic network conditions.

Findings

AutoRec reduces loss recovery latency significantly.

AutoRec adapts to network changes to maintain QoE.

AutoRec is practical and effective in real-world deployments.

Abstract

Due to the limited permissions for upgrading dualside (i.e., server-side and client-side) loss tolerance schemes from the perspective of CDN vendors in a multi-supplier market, modern large-scale live streaming services are still using the automatic-repeat-request (ARQ) based paradigm for loss recovery, which only requires server-side modifications. In this paper, we first conduct a large-scale measurement study with up to 50 million live streams. We find that loss shows dynamics and live streaming contains frequent on-off mode switching in the wild. We further find that the recovery latency, enlarged by the ubiquitous retransmission loss, is a critical factor affecting live streaming's client-side QoE (e.g., video freezing). We then propose an enhanced recovery mechanism called AutoRec, which can transform the disadvantages of on-off mode switching into an advantage for reducing loss recovery latency without any modifications on the client side. AutoRec allows users to customize overhead tolerance and recovery latency tolerance and adaptively adjusts strategies as the network environment changes to ensure that recovery latency meets user demands whenever possible while keeping overhead under control. We implement AutoRec upon QUIC and evaluate it via testbed and real-world commercial services deployments. The experimental results demonstrate the practicability and profitability of AutoRec.