NeTS: Small: Support for Interactive AR/VR Video: Learning and Optimizing at the Network Edge

NeTS：小型：支持交互式 AR/VR 视频：在网络边缘学习和优化

• 批准号: 1817216
• 负责人: Jiasi Chen
• 金额: $ 25万
• 依托单位: University of California-Riverside
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1817216&HistoricalAwards=false
• 关键词: NeTS; Small; Support; Interactive; AR

Augmented and virtual reality (AR/VR) are increasingly used in new application areas including entertainment, medicine, public safety, architecture, personnel training, etc. Mobile AR/VR systems allow users to be untethered, thus making it convenient for use in new settings. Edge networking and computing is a promising way to support demanding, low latency AR/VR applications, however there is a need for a deeper understanding of what functionality an edge system should provide to support those applications. This project improves user experience with AR/VR applications by using compute capability in edge cloud nodes located close to the user. The goal is to implement a system for real-time streaming and analysis of AR/VR videos that jointly uses the network efficiently while maintaining a high user Quality of Experience (QoE). The first activity is to develop a common set of functional building blocks that implement a set of generic AR/VR applications.The second goal is to develop the techniques to chain these building blocks together in a way that effectively uses an edge server composed of a mix of both set Central Processing Units (CPUs) and Graphics Processing Units (GPUs). An evaluation will be performed on a testbed of AR/VR devices and smartphones through trace-driven simulations, using publicly-available user datasets.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

增强现实和虚拟现实（AR/VR）越来越多地应用于娱乐、医疗、公共安全、建筑、人员培训等新应用领域。移动AR/VR系统让用户不受束缚，方便在新的领域使用。设置。边缘网络和计算是支持要求苛刻的低延迟 AR/VR 应用程序的一种有前途的方法，但是需要更深入地了解边缘系统应提供哪些功能来支持这些应用程序。该项目通过使用靠近用户的边缘云节点的计算能力来改善 AR/VR 应用程序的用户体验。目标是实现一个用于 AR/VR 视频实时流传输和分析的系统，该系统能够有效地联合使用网络，同时保持较高的用户体验质量 (QoE)。第一个活动是开发一组通用的功能构建块，用于实现一组通用 AR/VR 应用程序。第二个目标是开发将这些构建块链接在一起的技术，有效地使用由中央处理单元 (CPU) 和图形处理单元 (GPU) 的组合。 将使用公开的用户数据集，通过跟踪驱动的模拟，在 AR/VR 设备和智能手机的测试平台上进行评估。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优势和更广泛的评估进行评估，被认为值得支持。影响审查标准。

项目成果

Frugal following: power thrifty object detection and tracking for mobile augmented reality

节俭跟随：移动增强现实的节能对象检测和跟踪

• DOI: 10.1145/3356250.3360044
• 发表时间: 2019-11-10
• 期刊: Proceedings of the 17th Conference on Embedded Networked Sensor Systems
• 作者: Kittipat Apicharttrisorn;Xukan Ran;Jiasi Chen;S. Krishnamurthy;A. Roy
• 通讯作者: A. Roy

Viewing the 360° Future: Trade-Off Between User Field-of-View Prediction, Network Bandwidth, and Delay

展望 360° 未来：用户视野预测、网络带宽和延迟之间的权衡

• DOI: 10.1109/icccn49398.2020.9209659
• 发表时间: 2020-08-01
• 期刊: 2020 29th International Conference on Computer Communications and Networks (ICCCN)
• 作者: Shahryar Afzal;Jiasi Chen;K. K. Ramakrishnan
• 通讯作者: K. K. Ramakrishnan

Networked Architectures for Localization-Based Multi-User Augmented Reality

基于本地化的多用户增强现实的网络架构

• DOI: 10.1109/mcom.003.2300275
• 发表时间: 2023-12-01
• 期刊: IEEE Communications Magazine
• 影响因子: 11.2
• 作者: Jiasi Chen;K. K. Ramakrishnan;Aditya Dhakazl;Xukan Ran
• 通讯作者: Xukan Ran

ShareAR: Communication-Efficient Multi-User Mobile Augmented Reality

ShareAR：高效通信的多用户移动增强现实

• DOI: 10.1145/3365609.3365867
• 发表时间: 2019-11-13
• 期刊: Proceedings of the 18th ACM Workshop on Hot Topics in Networks
• 作者: Xukan Ran;Carter Slocum;M. Gorlatova;Jiasi Chen
• 通讯作者: Jiasi Chen

SLAM-share: visual simultaneous localization and mapping for real-time multi-user augmented reality

SLAM-share：实时多用户增强现实的视觉同步定位和建图

• DOI: 10.1145/3555050.3569142
• 发表时间: 2022-11-30
• 期刊: Proceedings of the 18th International Conference on emerging Networking EXperiments and Technologies
• 作者: Aditya Dhakal;Xukan Ran;Yunshu Wang;Jiasi Chen;K. Ramakrishnan;adhak
• 通讯作者: adhak