Extended reality (XR) is at the center of attraction in the research
community due to the emergence of augmented, mixed, and virtual reality
applications. The performance of such applications needs to be uptight to
maintain the requirements of latency, energy consumption, and freshness of
data. Therefore, a comprehensive performance analysis model is required to
assess the effectiveness of an XR application but is challenging to design due
to the dependence of the performance metrics on several difficult-to-model
parameters, such as computing resources and hardware utilization of XR and edge
devices, which are controlled by both their operating systems and the
application itself. Moreover, the heterogeneity in devices and wireless access
networks brings additional challenges in modeling. In this paper, we propose a
novel modeling framework for performance analysis of XR applications
considering edge-assisted wireless networks and validate the model with
experimental data collected from testbeds designed specifically for XR
applications. In addition, we present the challenges associated with
performance analysis modeling and present methods to overcome them in detail.
Finally, the performance evaluation shows that the proposed analytical model
can analyze XR applications' performance with high accuracy compared to the
state-of-the-art analytical models.

本文提出了一种新颖的建模框架，用于考虑边缘辅助无线网络的扩展现实应用的性能分析，并通过专门为扩展现实应用设计的测试平台收集的实验数据对模型进行验证。此外，我们详细介绍了与性能分析建模相关的挑战，并提出了克服这些挑战的方法。最后，性能评估表明，与现有的分析模型相比，所提出的分析模型可以以高精度分析扩展现实应用的性能。