NSF Award
2210744
Similar to cloud computing, edge computing also needs the support of virtualization in order to facilitate the effective management and efficient utilization. However, simply migrating traditional multi-layered virtualization from the cloud to the edge environment cannot fully utilize the flexibility, differentiation, and elasticity in edge platforms. First, there exists a significant gap of hardware constraint and energy sensitivity between cloud and edge systems. Second, too many virtualized layers introduce indirect and unnecessary expenses, resulting in unreasonable system structure and low efficiency. Third, the semantic gap between the edge runtime and various virtualization layers, as well as lack of coordination, hinders the adoption of virtualization on edge systems. This research addresses these issues and seeks to improve the performance, predictability, and energy-efficiency of virtualized edge systems. The research will also be tightly integrated into course teaching, project development, and further broaden its impacts through industrial collaboration, recruiting and mentoring minority students, and outreach activities in local K-12 schools.<br/><br/>This project will investigate the reasons for the inefficiency of virtualization in edge computing and explore the potential to unleash performance and improve energy consumption. Specifically, the project focuses on a multi-layered collaborative approach to virtualized edge systems and entails two research thrusts. First, it will rethink the collaboration between the edge hardware and software layers, so that the software-stack execution actively adapts to the edge-hardware dynamics, including energy consumption, real-time resource utilization, hardware heterogeneity, etc. Second, it will empower software collaboration between the virtualized application layer and OS system layer that can truly realize the efficiency and flexibility of virtualization on edge platforms.<br/><br/>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.
