EAVS: Edge-assisted Adaptive Video Streaming with Fine-grained Serverless Pipelines

EAVS: Edge-assisted Adaptive Video Streaming with Fine-grained Serverless Pipelines

Hou, Biao (Beijing Institute of Technology)
Yang, Song (Beijing Institute of Technology)
Kuipers, F.A. (TU Delft Networked Systems)
Jiao, Lei (University of Oregon)
Fu, Xiaoming (University of Göttingen)

2023

Recent years have witnessed video streaming grad- ually evolve into one of the most popular Internet applications. With the rapidly growing personalized demand for real-time video streaming services, maximizing their Quality of Experience (QoE) is a long-standing challenge. The emergence of the server- less computing paradigm has potential to meet this challenge through its fine-grained management and highly parallel comput- ing structures. However, it is still ambiguous how to implement and configure serverless components to optimize video streaming services. In this paper, we propose EAVS, an Edge-assisted Adaptive Video streaming system with Serverless pipelines, which facilitates fine-grained management for multiple concurrent video transmission pipelines. Then, we design a chunk-level optimiza- tion scheme to address video bitrate adaptation. We propose a Deep Reinforcement Learning (DRL) algorithm based on Proximal Policy Optimization (PPO) with a trinal-clip mechanism to make bitrate decisions efficiently for better QoE. Finally, we implement the serverless video streaming system prototype and evaluate the performance of EAVS on various real-world network traces. Our results show that EAVS significantly improves QoE and reduces the video stall rate, achieving over 9.1% QoE improvement and 60.2% latency reduction compared to state- of-the-art solutions.

Video streaming
Serverless computing
Deep reinforcement learning
Quality of Experience

http://resolver.tudelft.nl/uuid:75c07e94-6cc7-46a6-b68d-ad3c8edb921e

https://doi.org/10.1109/INFOCOM53939.2023.10229102

IEEE, Danvers

2024-02-29

979-8-3503-3415-9

Proceedings of the INFOCOM 2023 - IEEE International Conference on Computer Communications

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications, 2023-05-17 → 2023-05-20, New York City, United States

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

conference paper

© 2023 Biao Hou, Song Yang, F.A. Kuipers, Lei Jiao, Xiaoming Fu