SHF: Small: Towards High Performance Serverless Edge Computing for Data-intensive Applications

SHF：小型：面向数据密集型应用程序的高性能无服务器边缘计算

• 批准号: 2230620
• 负责人: Yuanyuan Yang
• 金额: $ 60万
• 依托单位: SUNY at Stony Brook
• 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: 2022-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2230620&HistoricalAwards=false
• 关键词: SHF; Small; Towards; Performance; Serverless

Edge computing has become an indispensable booster for the rapid development of Internet-of-Things. It provides users not only low-delay and high-bandwidth services but also unprecedented security and privacy guarantee. However, the unique challenges of network edge, such as resource limitation and device heterogeneity, greatly increase the difficulty of developing and managing edge applications. Researchers have turned to emerging serverless computing paradigm for efficient and cost-effective solutions. The light-weight virtualization of serverless edge computing largely mitigates the resource shortage of edge environments while providing extra flexibility. Furthermore, edge application developers are completely liberated from complicated management of edge resources, facilitating the portability and short time-to-market of edge applications. Nevertheless, serverless edge computing is still impeded by the inherent natures of network edge. The computation/data geo-dispersion and device heterogeneity in edge environments may introduce long transmission and computation delay to the initialization and execution of data-intensive edge functions. The resource limitation and volatile network conditions further exacerbate the negative impact and increase the risk of network congestion. This project aims to systematically investigate the challenging issues towards building a high performance serverless edge computing framework for data-intensive applications. This project provides a hardware/software co-design to construct a novel serverless edge computing framework for data-intensive applications. More specifically, it consists of following inter-related research tasks: (1) develop a hardware-enhanced architecture for accelerating data processing, transmission and distribution of serverless edge computing; (2) design a data-aware computation orchestration system that adapts to unique edge conditions and the data acceleration architecture; (3) develop a computation-aware data orchestration system that adjusts the data acceleration architecture dynamically; (4) conduct a comprehensive performance evaluation through extensive simulations and implementation of a prototype of the framework. The outcome of this project will not only enhance the performance of many current data-intensive edge functions, but also facilitate the edge adoption for numerous future applications that rely on efficient data processing and transmission. As edge computing is penetrating into all aspects of human lives, this research will have a profound impact on the society. The project trains graduate students and promotes the participation of female students in computer engineering. The important findings of this project will be integrated into a graduate course and disseminated to research community and industry by way of conferences, journals and website access.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.

边缘计算已成为物联网快速发展不可或缺的助推器。它为用户提供的不仅是低时延、高带宽的服务，还提供前所未有的安全和隐私保障。然而，网络边缘的独特挑战，例如资源限制和设备异构性，大大增加了边缘应用的开发和管理难度。研究人员已转向新兴的无服务器计算范式，以寻求高效且经济高效的解决方案。无服务器边缘计算的轻量级虚拟化在很大程度上缓解了边缘环境的资源短缺问题，同时提供了额外的灵活性。此外，边缘应用开发者完全从复杂的边缘资源管理中解放出来，有利于边缘应用的可移植性和缩短上市时间。尽管如此，无服务器边缘计算仍然受到网络边缘固有特性的阻碍。边缘环境中的计算/数据地理分散性和设备异构性可能会给数据密集型边缘功能的初始化和执行带来较长的传输和计算延迟。资源限制和网络状况的不稳定进一步加剧了负面影响并增加了网络拥塞的风险。该项目旨在系统地研究为数据密集型应用程序构建高性能无服务器边缘计算框架的挑战性问题。该项目提供了一种硬件/软件协同设计，为数据密集型应用程序构建新型无服务器边缘计算框架。更具体地说，它包括以下相互关联的研究任务：（1）开发硬件增强架构，用于加速无服务器边缘计算的数据处理、传输和分发； （2）设计适应独特边缘条件的数据感知计算编排系统和数据加速架构； （3）开发计算感知的数据编排系统，动态调整数据加速架构； (4)通过广泛的模拟和框架原型的实现来进行全面的性能评估。该项目的成果不仅将增强当前许多数据密集型边缘功能的性能，还将促进依赖高效数据处理和传输的众多未来应用程序的边缘采用。随着边缘计算正在渗透到人类生活的各个方面，这项研究将对社会产生深远的影响。该项目培养研究生并促进女学生参与计算机工程。该项目的重要发现将被纳入研究生课程，并通过会议、期刊和网站访问的方式传播给研究界和行业。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值进行评估，被认为值得支持以及更广泛的影响审查标准。