Fog Computing for Augmented Reality: Trends, Challenges and Opportunities

S. Salman, T. Sitompul, A. Papadopoulos, T. Nolte
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引用次数: 7

Abstract

Augmented reality applications are computationally intensive and have latency requirements in the range of 15- 20 milliseconds. Fog computing addresses these requirements by providing on-demand computing capacity and lower latency by bringing the computational resources closer to the augmented reality devices. In this paper, we reviewed papers providing custom solutions for augmented reality using the fog architecture and identified that the ongoing research trends towards balancing quality-of-experience, energy, and latency for both single and collaborative multi-device augmented reality applications. Furthermore, some works also focus on providing architectures for fog-based augmented reality systems and also on the training of machine learning algorithms in the fog layers to improve user experience. Based on these findings, we provide some challenges and research directions that can facilitate the adoption of fog-based augmented reality systems.
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增强现实的雾计算:趋势、挑战和机遇
增强现实应用是计算密集型的,并且延迟要求在15- 20毫秒之间。雾计算通过使计算资源更接近增强现实设备,从而提供按需计算能力和更低的延迟,从而满足了这些需求。在本文中,我们回顾了使用雾架构为增强现实提供定制解决方案的论文,并确定了正在进行的研究趋势是平衡单设备和协作多设备增强现实应用的体验质量、能量和延迟。此外,一些工作还专注于为基于雾的增强现实系统提供架构,以及在雾层中训练机器学习算法以改善用户体验。基于这些发现,我们提出了一些挑战和研究方向,可以促进基于雾的增强现实系统的采用。
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tinyFaaS: A Lightweight FaaS Platform for Edge Environments ICFC 2020 Commentary Fog Computing for Augmented Reality: Trends, Challenges and Opportunities ICFC 2020 Index [Copyright notice]
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