research-article

Fine-grained Caching and Resource Scheduling for Adaptive Bitrate Videos in Edge Networks

Authors:

Chaocan XiangAuthors Info & Claims

ACM Transactions on Sensor Networks, Volume 19, Issue 4

Article No.: 95, Pages 1 - 30

https://doi.org/10.1145/3604555

Published: 10 July 2023 Publication History

Abstract

With the easy access to mobile networks and the proliferation of video applications, video traffic is occupying a great portion of the network traffic, which poses a new challenge of how to alleviate the heavy backhaul traffic and ensure the high quality of experience for video services. As a promising solution towards addressing this challenge, video caching in edge networks has recently received significant attention, which mostly considers the video popularity and the user preference for the video. However, few studies consider the user behavior and the user preference for different parts of the video that indeed have an essential impact on caching efficiency. Hence, this article proposes a new caching and resource scheduling scheme for adaptive bitrate videos by incorporating these fine-grained factors. We first model the video service problem as a nonlinear integer programming problem, which can be divided into a cache placement problem and an online resource scheduling problem. Then, we design efficient algorithms based on several techniques, including greedy strategy, relaxation, and rounding, to solve the two problems. Extensive experimental results based on two real-world datasets show that the proposed solution achieves superior performance compared with several state-of-the-art caching approaches.

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Index Terms

Fine-grained Caching and Resource Scheduling for Adaptive Bitrate Videos in Edge Networks
1. Computing methodologies
  1. Modeling and simulation
2. Networks
  1. Network services

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cover image ACM Transactions on Sensor Networks

ACM Transactions on Sensor Networks Volume 19, Issue 4

November 2023

622 pages

ISSN:1550-4859

EISSN:1550-4867

DOI:10.1145/3593034

Editor:
Yunhao Liu
Tsinghua University, China

Issue’s Table of Contents

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ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 10 July 2023

Online AM: 12 June 2023

Accepted: 08 June 2023

Revised: 06 June 2023

Received: 22 September 2022

Published in TOSN Volume 19, Issue 4

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Zhu YZheng YLiu JLi YZha Z(2024)Noise-Resistance Learning via Multi-Granularity Consistency for Unsupervised Domain Adaptive Person Re-IdentificationACM Transactions on Multimedia Computing, Communications, and Applications10.1145/370232821:1(1-23)Online publication date: 2-Nov-2024
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