SHF: Small: Rethinking Virtualization at the Edge to Support Highly-efficient and Low-power Applications

SHF：小型：重新思考边缘虚拟化以支持高效和低功耗应用

• 批准号: 2210744
• 负责人: Kun Suo
• 金额: $ 32.51万
• 依托单位: Kennesaw State University Research and Service Foundation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2210744&HistoricalAwards=false
• 关键词: SHF; Small; Rethinking; Virtualization; Edge

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.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.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.

与云计算类似，边缘计算也需要虚拟化的支持，以便于有效管理和高效利用。然而，简单地将传统的多层虚拟化从云端迁移到边缘环境并不能充分利用边缘平台的灵活性、差异性和弹性。首先，云端和边缘系统之间在硬件约束和能源敏感性方面存在显着差距。其次，过多的虚拟化层引入了间接的、不必要的开支，导致系统结构不合理，效率低下。第三，边缘运行时和各个虚拟化层之间的语义差距以及缺乏协调阻碍了虚拟化在边缘系统上的采用。这项研究解决了这些问题，并寻求提高虚拟化边缘系统的性能、可预测性和能源效率。该研究还将紧密融入课程教学、项目开发，并通过行业合作、招募和指导少数族裔学生以及当地 K-12 学校的推广活动进一步扩大其影响。该项目将调查边缘计算虚拟化效率低下的原因，并探索释放性能和改善能耗的潜力。具体来说，该项目侧重于虚拟化边缘系统的多层协作方法，并需要两个研究重点。首先，它将重新思考边缘硬件和软件层之间的协作，使软件堆栈执行主动适应边缘硬件动态，包括能耗、实时资源利用率、硬件异构性等。其次，它将赋能虚拟化应用层和操作系统层之间的软件协作，真正实现边缘平台虚拟化的高效性和灵活性。该奖项体现了 NSF 的法定使命， 通过使用基金会的智力优点和更广泛的影响审查标准进行评估，认为值得支持。