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: 2212098
• 负责人: Ahmed Saeed
• 金额: $ 74.81万
• 依托单位: Georgia Tech Research Corporation
• 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=2212098&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.

边缘计算有助于现代数字经济的许多部门的增长，从企业IT和通信到智能城市、制造业和医疗保健。通过以区域或微型数据中心(UDC)的形式使资源更接近最终用户，边缘计算支持具有极低延迟和高带宽需求的新应用。本项目考虑边缘服务器的终端-主机网络堆栈的设计。因此，从成本和性能两方面考虑，最大限度地利用有限的UDC资源至关重要，这促使我们重新审视当今EDGE中使用的软件和硬件层。这个项目将遵循软件/硬件协同设计的方法。该项目将专注于减少资源调度和状态管理功能的开销，改进这些功能在堆栈中的分布方式。最终目标是最大限度地减少执行这些功能所浪费的CPU时间，反之，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，边缘计算将支持新的应用类别，而当前云中的效用计算范例不适合这些应用。这些应用包括对延迟高度敏感的应用(例如，5G、情景感知应用、增强现实、自动驾驶车辆和在线游戏)或对带宽要求很高的应用(例如，摄像头网络和视频分析)。因此，预计边缘计算将沿着云计算的轨迹，在未来五到七年内成长为一个数十亿美元的产业。该项目的成果有可能改变现代社会运行和使用这一至关重要且快速增长的互联网基础设施的方式。该项目旨在显著提高EDGE性能和成本效益，使供应商能够最大限度地利用稀缺的EDGE资源，使开发商能够执行以前不可行的计算要求高的任务。在这个项目中开发的研究将被整合到本科生、研究生和在线课程中。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

A Characterization of Route Variability in LEO Satellite Networks

• DOI: 10.1007/978-3-031-28486-1_14
• 发表时间: 2023
• 期刊: Optometry and Vision Science
• 影响因子: 1.4
• 作者: Vaibhav Bhosale;Ahmed Saeed;Ketan Bhardwaj;Ada Gavrilovska

Protego: Overload Control for Applications with Unpredictable Lock Contention

• 发表时间: 2023
• 作者: Inho Cho;Ahmed Saeed;S. Park;Mohammad Alizadeh;A. Belay