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PLVER: Joint Stable Allocation and Content Replication for Edge-Assisted Live Video Delivery

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

Abstract

Live streaming services have gained extreme popularity in recent years. Due to the spiky traffic patterns of live videos, utilizing distributed edge servers to improve viewers' quality of experience (QoE) has become a common practice nowadays. Nevertheless, the current client-driven content caching mechanism does not support pre-caching from the cloud to the edge, resulting in a considerable amount of cache misses in live video delivery. By jointly considering the features of live videos and edge servers, we propose PLVER, a proactive live video push scheme to address the cache miss problem in live video delivery. Specifically, PLVER first conducts a one-To-multiple stable allocation between edge clusters and user groups to balance the load of live traffic over the edge servers. It then adopts proactive video replication algorithms to speed up video replication among the edge servers. We conduct extensive trace-driven evaluation, covering 0.3 million Twitch viewers and more than 300 Twitch channels. The results demonstrate that with PLVER, edge servers can carry 28 and 82 percent more traffic than the auction-based replication (ABR) method and the caching on requested time (CORT) method, respectively.
Original languageEnglish
Article number9462365
Pages (from-to)218-230
JournalIEEE Transactions on Parallel and Distributed Systems
Volume33
Issue number1
Online published22 Jun 2021
DOIs
Publication statusPublished - Jan 2022

Research Keywords

  • edge computing
  • Live video streaming
  • proactive video replication
  • stable one-to-multiple allocation

RGC Funding Information

  • RGC-funded

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