移动边缘计算下基于无线虚拟现实的多媒体辅助教学系统框架

W. Cui, Ding Eng Na, Yuting Zhang
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引用次数: 0

摘要

近年来,虚拟现实(VR)从单纯的科学研究逐渐进入到日常的教育教学活动中。在辅助教学领域,一些典型的计算机软件仍然发挥着重要的作用。这使得远程教学活动只能学习语音,而不能拥有现实存在的感觉。特别是在新冠肺炎疫情背景下,迫切需要有针对性的远程教学活动。针对这一挑战,本文提出了一种移动边缘计算网络下基于无线vr的多媒体辅助教学系统框架。该框架采用基于视口预测的协同边缘缓存和自适应流,共同提高VR用户的体验质量。首先,我们研究了该框架中缓存和自适应流的资源管理问题。考虑到公式化问题的复杂性,提出了一种分布式学习方案来解决问题。对实验数据进行了验证,实验结果证明所研究的方法提高了用户QoE的性能。[源自作者]
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Wireless Virtual Reality-Based Multimedia-Assisted Teaching System Framework under Mobile Edge Computing
In recent years, virtual reality (VR) has gradually entered the daily education and teaching activities from pure scientific research. In the area of assistance teaching, some typical computer softwares still play some important roles. This makes remote teaching activities can just learn voice, yet cannot possess the feeling of realistic existence. Especially in scenario of COVID-19, remote teaching activities with proper perceptibility are in urgent demand. To deal with the current challenge, this paper proposes a wireless VR-based multimedia-assisted teaching system framework under mobile edge computing networks. In this framework, cooperative edge caching and adaptive streaming based on viewport prediction are adopted to jointly improve the quality of experience (QoE) of VR users. First, we investigated the resource management problem of caching and adaptive streaming in this framework. Considering the complexity of the formulated problem, a distributed learning scheme is proposed to solve the problem. The experimental data are verified and the experimental results prove that the studied methods improve the performance of user QoE. [ FROM AUTHOR]
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