Proactive Edge Computing for Video Streaming: A Mutual Conversion Model for Varying Requirements on Representations

XIONG Guangzheng; DAI Zhitao

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Proactive Edge Computing for Video Streaming: A Mutual Conversion Model for Varying Requirements on Representations

XIONG Guangzheng,DAI Zhitao *

School of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876

*Correspondence author

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Funding: none

Opened online:11 November 2022

Accepted by: none

Citation: XIONG Guangzheng,DAI Zhitao.Proactive Edge Computing for Video Streaming: A Mutual Conversion Model for Varying Requirements on Representations[OL]. [11 November 2022] http://en.paper.edu.cn/en_releasepaper/content/4758328

The vast proliferation of video streaming traffic imposed unprecedented challenges to origin servers in the Core Network (CN), further exacerbated by the diversity of requirements on video encoding format, resolution, and frame rate. Multi-access Edge Computing (MEC) has been introduced to mitigate the problem by storing and transcoding videos at the network edges to reduce traffic to CN. This work proposes a novel mutual conversion model with a conversion graph among representations by applying the space-time video super-resolution (STVSR) algorithm and transcoding on edge servers. These mutual conversions generate high-definition representations from lower ones and vice versa. The model measures and estimates the qualities of conversion outputs to maintain high Quality of Experience (QoE). Moreover, an off-peak proactive cache replacement algorithm is introduced to utilize the remaining resources by prefetching and pre-converting popular representations, capturing the trend of clients' interests. Transmission history between the edge servers and clients is collected to predict bandwidth and calculate playback buffer length. The experimental results demonstrate that the proposed approach significantly reduces traffic to the origin server while achieving high QoE.

Keywords:edge computing; video streaming; proactive caching; vidoe transcoding; video super-resolution

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