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、人员培训等新的应用领域。移动AR/VR系统允许用户不受限制，从而方便在新环境中使用。边缘网络和计算是支持要求高、低延迟的AR/VR应用的一种很有前途的方式，但是需要更深入地了解边缘系统应该提供哪些功能来支持这些应用。该项目通过在靠近用户的边缘云节点中使用计算能力来改善AR/VR应用程序的用户体验。目标是实现一个实时流媒体和AR/VR视频分析系统，该系统可以有效地共同使用网络，同时保持高用户体验质量（QoE）。第一个活动是开发一组通用的功能构建块，实现一组通用的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，以一种有效地使用由中央处理单元（cpu）和图形处理单元（gpu）混合组成的边缘服务器的方式。评估将在AR/VR设备和智能手机的测试平台上进行，通过追踪驱动的模拟，使用公开可用的用户数据集。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Networked Architectures for Localization-Based Multi-User Augmented Reality

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

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

• DOI: 10.1145/3555050.3569142
• 发表时间: 2022-11
• 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

ShareAR: Communication-Efficient Multi-User Mobile Augmented Reality

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

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

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

Multi-user augmented reality with communication efficient and spatially consistent virtual objects

• DOI: 10.1145/3386367.3431312
• 发表时间: 2020-11
• 期刊: Proceedings of the 16th International Conference on emerging Networking EXperiments and Technologies
• 作者: Xukan Ran;Carter Slocum;Yi-Zhen Tsai;Kittipat Apicharttrisorn;M. Gorlatova;Jiasi Chen