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.

Agency
National Science Foundation (NSF)
Institute
Division of Computer and Network Systems (CNS)
Type
Standard Grant (Standard)
Application #
1817216
Program Officer
Deepankar Medhi
Project Start
Project End
Budget Start
2018-10-01
Budget End
2021-09-30
Support Year
Fiscal Year
2018
Total Cost
$250,000
Indirect Cost
Name
University of California Riverside
Department
Type
DUNS #
City
Riverside
State
CA
Country
United States
Zip Code
92521