Collaborative Research: CNS Core: Medium: High-performance Network Stacks for the Edge

合作研究：CNS 核心：中：边缘的高性能网络堆栈

• 批准号: 2212099
• 负责人: Adam Belay
• 金额: $ 45万
• 依托单位: Massachusetts Institute of Technology
• 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=2212099&HistoricalAwards=false
• 关键词: Collaborative; Research; CNS; Core; Medium

Edge computing is instrumental to the growth of many sectors of modern digital economies, ranging from enterprise IT and communication, to smart cities, manufacturing, and healthcare. By bringing resources closer to end users in the form of regional or micro-datacenters (uDCs), edge computing enables new applications with extreme low-latency and high-bandwidth demands. This project considers the design of the end-host networking stack for edge servers. Maximizing utilization of the limited uDC resources is therefore critical for both cost and performance reasons, motivating us to revisit the software and hardware layers that are used in the edge today. This project will follow a software/hardware co-design approach. The project will focus on reducing the overhead of resource scheduling and state management functions, revamping the way these functions are distributed across the stack. The ultimate objective is to minimize the CPU time wasted performing these functions, conversely maximizing the compute resources available to handle application logic. With the right innovation to overcome current obstacles, edge computing will enable new classes of applications that the current paradigm of utility computing in the Cloud is ill-suited for. These include applications that are highly sensitive to latency (e.g., 5G, situation-awareness applications, augmented reality, autonomous vehicles, and online gaming) or have heavy bandwidth demands (e.g., camera networks and video analytics). It is therefore expected that edge computing will follow the trajectory of Cloud computing and grow to a multi-billion-dollar industry within the next five to seven years. The project’s outcomes have the potential to transform the way modern societies operate and use this critically important and rapidly growing piece of internet infrastructure. The project aims to dramatically improve edge performance and cost efficiency, allowing providers to maximize the utility of scarce edge resources and developers to perform computationally demanding tasks that were previously infeasible. The research developed in this project will be integrated into undergraduate, graduate, and online courses.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.

边缘计算对现代数字经济的许多领域的增长至关重要，从企业IT和沟通到智能城市，制造业和医疗保健。通过将资源以区域或微型数据（UDCS）的形式与最终用户更接近，Edge Computing可以实现具有极端低延迟和高带宽需求的新应用程序。该项目考虑了边缘服务器的最终宿主网络堆栈的设计。因此，出于成本和绩效原因，最大化有限UDC资源的利用至关重要，激励我们重新审视当今优势使用的软件和硬件层。该项目将遵循软件/硬件共同设计方法。该项目将着重于减少资源调度和状态管理功能的开销，对这些功能分布在整个堆栈中的方式进行改进。最终目标是最大程度地减少执行这些功能的CPU时间浪费，相反，最大化可用于处理应用程序逻辑的计算资源。通过正确的创新来克服当前的障碍，Edge Computing将使云中当前实用程序计算的当前实用程序范式不适合使用新的应用程序。这些应用程序包括对延迟高度敏感的应用程序（例如5G，情境意识应用程序，增强现实，自动驾驶汽车和在线游戏）或具有较重的带宽需求（例如，摄像机网络和视频分析）。因此，预计边缘计算将遵循云计算的轨迹，并在未来五到七年内发展到数十亿美元的行业。该项目的成果有可能改变现代社会运作和使用这一至关重要且快速发展的互联网基础设施的方式。该项目旨在极大地提高优势性能和成本效率，使提供商能够最大程度地提高稀缺边缘资源和开发人员的效用，并执行以前不可行的计算要求的任务。该项目中开发的研究将纳入本科，研究生和在线课程。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子优点和更广泛的影响审查标准来评估诚实地通过评估来诚实。