Edge-based Transcoding for Adaptive Live Video Streaming

Authors: 

Pradeep Dogga, UCLA; Sandip Chakraborty, IIT Kharagpur; Subrata Mitra, Adobe Research; Ravi Netravali, UCLA

Abstract: 

User-generated video content is imposing an increasing burden on live video service architectures such as Facebook Live. These services are responsible for ingesting large amounts of video, transcoding that video into different quality levels (i.e., bitrates), and adaptively streaming it to viewers. These tasks are expensive, both computationally and network-wise, often forcing service providers to sacrifice the “liveness” of delivered video. Given the steady increases in smartphone bandwidth and energy resources, coupled with the fact that commodity smartphones now include hardware-accelerated codecs, we propose that live video services augment their existing infrastructure with edge support for transcoding and transmission. We present measurements to motivate the feasibility of incorporating such edge-support into the live video ecosystem, present the design of a peer-to-peer adaptive live video streaming system, and discuss directions for future work to realize this vision in practice.

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BibTeX
@inproceedings {234793,
author = {Pradeep Dogga and Sandip Chakraborty and Subrata Mitra and Ravi Netravali},
title = {Edge-based Transcoding for Adaptive Live Video Streaming},
booktitle = {2nd {USENIX} Workshop on Hot Topics in Edge Computing (HotEdge 19)},
year = {2019},
address = {Renton, WA},
url = {https://www.usenix.org/conference/hotedge19/presentation/dogga},
publisher = {{USENIX} Association},
month = jul,
}