In recent years, advances in immersive multimedia technologies, such as extended reality (XR) technologies, have led to more realistic and user-friendly devices. However, these devices are often bulky and uncomfortable, still requiring tether connectivity for demanding applications. The deployment of the fifth generation of telecommunications technologies (5G) has set the basis for XR offloading solutions with the goal of enabling lighter and fully wearable XR devices. In this paper, we present a traffic dataset for two demanding XR offloading scenarios that are complementary to those available in the current state of the art, captured using a fully developed end-to-end XR offloading solution. We also propose a set of accurate traffic models for the proposed scenarios based on the captured data, accompanied by a simple and consistent method to generate synthetic data from the fitted models. Finally, using an open-source 5G radio access network (RAN) emulator, we validate the models both at the application and resource allocation layers. Overall, this work aims to provide a valuable contribution to the field with data and tools for designing, testing, improving, and extending XR offloading solutions in academia and industry.
翻译:近年来,诸如扩展现实(XR)技术等隐性多媒体技术的进步导致更现实和更方便用户的装置,然而,这些装置往往体积大、不舒服,仍然需要绳索连通,以达到要求的应用程序。第五代电信技术(5G)的部署为XR卸载解决方案奠定了基础,目的是能够更轻和充分磨损的XR设备。在本文件中,我们为两种要求很高的XR卸载情景提供了一个交通数据集,这些数据集与目前最新技术中的现有情景互为补充,是利用充分开发的端到端的XR卸载解决方案收集的。我们还根据所采集的数据为拟议的设想情景提出了一套准确的交通模式,同时采用简单一致的方法从安装的模型中生成合成数据。最后,我们使用开放源的5G无线电接入网络(RAN)模拟器,验证了应用和资源配置层的模型。总体而言,这项工作旨在为实地提供宝贵的数据及工具,用于设计、测试、改进和扩大学术界和工业界XR卸载解决方案。