Intelligent cache and buffer optimization for mobile VR adaptive transmission in 5G edge computing networks

IF 7.5 2区 计算机科学 Q1 TELECOMMUNICATIONS Digital Communications and Networks Pub Date : 2024-10-01 DOI:10.1016/j.dcan.2023.07.003
Junchao Yang , Ali Kashif Bashir , Zhiwei Guo , Keping Yu , Mohsen Guizani
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Abstract

Virtual Reality (VR) is a key industry for the development of the digital economy in the future. Mobile VR has advantages in terms of mobility, lightweight and cost-effectiveness, which has gradually become the mainstream implementation of VR. In this paper, a mobile VR video adaptive transmission mechanism based on intelligent caching and hierarchical buffering strategy in Mobile Edge Computing (MEC)-equipped 5G networks is proposed, aiming at the low latency requirements of mobile VR services and flexible buffer management for VR video adaptive transmission. To support VR content proactive caching and intelligent buffer management, users' behavioral similarity and head movement trajectory are jointly used for viewpoint prediction. The tile-based content is proactively cached in the MEC nodes based on the popularity of the VR content. Second, a hierarchical buffer-based adaptive update algorithm is presented, which jointly considers bandwidth, buffer, and predicted viewpoint status to update the tile chunk in client buffer. Then, according to the decomposition of the problem, the buffer update problem is modeled as an optimization problem, and the corresponding solution algorithms are presented. Finally, the simulation results show that the adaptive caching algorithm based on 5G intelligent edge and hierarchical buffer strategy can improve the user experience in the case of bandwidth fluctuations, and the proposed viewpoint prediction method can significantly improve the accuracy of viewpoint prediction by 15%.
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5G边缘计算网络下移动VR自适应传输的智能缓存与缓冲优化
虚拟现实(VR)是未来数字经济发展的关键产业。移动 VR 具有移动性、轻便性和高性价比等优势,已逐渐成为 VR 的主流实现方式。本文针对移动VR业务的低时延要求和VR视频自适应传输的灵活缓冲管理,提出了一种基于移动边缘计算(MEC)的5G网络中智能缓存和分层缓冲策略的移动VR视频自适应传输机制。为了支持 VR 内容的主动缓存和智能缓冲管理,用户的行为相似性和头部移动轨迹被联合用于视点预测。根据 VR 内容的受欢迎程度,在 MEC 节点中主动缓存基于磁贴的内容。其次,提出了一种基于分层缓冲区的自适应更新算法,该算法联合考虑带宽、缓冲区和预测的视点状态来更新客户端缓冲区中的磁贴块。然后,根据问题的分解,将缓冲区更新问题建模为优化问题,并给出了相应的求解算法。最后,仿真结果表明,基于 5G 智能边缘和分层缓冲策略的自适应缓存算法可以改善带宽波动情况下的用户体验,而提出的视点预测方法可以将视点预测的准确率显著提高 15%。
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来源期刊
Digital Communications and Networks
Digital Communications and Networks Computer Science-Hardware and Architecture
CiteScore
12.80
自引率
5.10%
发文量
915
审稿时长
30 weeks
期刊介绍: Digital Communications and Networks is a prestigious journal that emphasizes on communication systems and networks. We publish only top-notch original articles and authoritative reviews, which undergo rigorous peer-review. We are proud to announce that all our articles are fully Open Access and can be accessed on ScienceDirect. Our journal is recognized and indexed by eminent databases such as the Science Citation Index Expanded (SCIE) and Scopus. In addition to regular articles, we may also consider exceptional conference papers that have been significantly expanded. Furthermore, we periodically release special issues that focus on specific aspects of the field. In conclusion, Digital Communications and Networks is a leading journal that guarantees exceptional quality and accessibility for researchers and scholars in the field of communication systems and networks.
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