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

Biao Hou, Song Yang, Fernando A. Kuipers, Lei Jiao, Xiaoming Fu

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

1 Citation (Scopus)
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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.
Original languageEnglish
Title of host publicationProceedings of the INFOCOM 2023 - IEEE International Conference on Computer Communications
Place of PublicationDanvers
Number of pages10
ISBN (Electronic)979-8-3503-3414-2
ISBN (Print)979-8-3503-3415-9
Publication statusPublished - 2023
Event IEEE INFOCOM 2023 - IEEE Conference on Computer Communications - New York City, United States
Duration: 17 May 202320 May 2023


Conference IEEE INFOCOM 2023 - IEEE Conference on Computer Communications
Country/TerritoryUnited States
CityNew York City

Bibliographical note

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.


  • Video streaming
  • Serverless computing
  • Deep reinforcement learning
  • Quality of Experience

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