CAREER: WolfPack: An Application-Network Co-Design Framework for Performance-Guaranteed Real-time Applications at the Network Edge

职业：WolfPack：用于网络边缘性能保证的实时应用程序的应用程序网络协同设计框架

• 批准号: 2045539
• 负责人: Ruozhou Yu
• 金额: $ 50.57万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2045539&HistoricalAwards=false
• 关键词: CAREER; WolfPack; Application; Network; Co

Distributed real-time applications constitute the core of many life-changing technologies. To satisfy the real-time requirement of such applications, edge computing provides a low-latency and high-throughput computing environment near the end devices and users. However, the complex structures of modern applications significantly hinder providing end-to-end real-time guarantee to these applications, especially in face of the also complex structures and dynamic nature of various edge computing networks. This project investigates the joint optimization and configuration of edge applications and the edge network, for providing end-to-end performance guarantee to modern distributed real-time applications.Specifically, this CAREER project aims to co-design the provisioning of both computing and network resources in edge computing, to provide end-to-end performance guarantee for a wide range of applications and edge network scenarios under a general optimization framework named the WolfPack. The project will focus on three complementary research thrusts: (i) a general packing-based optimization framework for applications and edge networks with arbitrary structures, (ii) a set of modeling and algorithmic tools for handling risks and providing robustness in face of application and network dynamics, and (iii) economic mechanisms for incentivized edge resource provisioning with performance guarantees. Collectively, the outcomes of this research will contribute to not only the core knowledge of edge resource management and performance guarantee, but also the literature of packing/covering optimization, truthful mechanism design, and optimization-based system design.The research component of this project will empower life-changing real-time applications that benefit citizens and society, including but not limited to smart city, connected industry, autonomous driving. The research outcomes will be broadly disseminated through journal/conference publications, tutorial papers, public talks, research seminars, and course teaching. Research is closely integrated with education to advance the curriculum of undergraduate and graduate education with renewed materials and practical teaching tools, promote active STEM research by students in K-12 through postgraduate levels, and increase awareness and participation in computing from female and underrepresented students. All research artifacts and outcomes of this project will be publicly available on the project website (https://people.engr.ncsu.edu/ryu5/project_wolfpack.php). The website will be actively maintained for at least the entire period of this project (five years), and also routinely updated after the end of this project to include further research advances following from this research.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.

分布式的实时应用构成了许多改变生命的技术的核心。为了满足此类应用程序的实时要求，Edge Computing在端设备和用户附近提供了低延迟和高通量计算环境。但是，现代应用程序的复杂结构极大地阻碍了这些应用程序的端到端实时保证，尤其是面对各种边缘计算网络的复杂结构和动态性质。该项目调查了边缘应用程序和边缘网络的联合优化和配置，以为现代分布式的实时应用程序提供端到端性能保证。特别是，该职业项目旨在共同设计在边缘计算中计算和网络资源的配置，以在应用程序和边缘网络场景中提供端到端的绩效保证，以提供广泛的应用程序和Edge网络风景范围，该范围却是一般性优化范围。该项目将着重于三个互补的研究推力：（i）具有任意结构的应用程序和边缘网络的一般优化框架，（ii）一组建模和算法工具，用于处理风险并在面对应用和网络动态方面提供鲁棒性，以及（III），（iii）具有绩效提供绩效保证的经济机制。总的来说，这项研究的结果不仅将有助于边缘资源管理和绩效保证的核心知识，而且还将有助于包装/涵盖/涵盖优化，真实的机制设计以及基于优化的系统设计的文献。该项目的研究组成部分将增强改变生活的实时应用，从而使公民和社会受益，包括但不限于Smart City，Connected Industry Industry Industry Industry Industry Industrys驾驶，自动驾驶。研究成果将通过期刊/会议出版物，教程论文，公开谈判，研究研讨会和课程教学广泛传播。研究与教育密切相结合，以通过新的材料和实用的教学工具来推进本科和研究生教育的课程，从而促进K-12学生通过研究生水平的学生进行积极的STEM研究，并提高女性和代表性不足的学生的认识和参与计算。该项目的所有研究工件和结果将在项目网站（https://people.engr.ncsu.edu/ryu/ryu5/project_wolfpack.php）上公开获得。该网站将至少在本项目的整个期间（五年）进行积极维护，并且在本项目结束后也经常更新，包括此研究之后的进一步研究进展。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的审查标准来通过评估来支持的。

项目成果

VeriEdge: Verifying and Enforcing Service Level Agreements for Pervasive Edge Computing

VeriEdge：验证和执行普适边缘计算的服务级别协议

• 发表时间: 2023
• 期刊: IEEE International Conference on Computer Communications (INFOCOM
• 作者: Wang, Xiaojian;Yu, Ruozhou;Yang, Dejun;Gu, Huayue;Li, Zhouyu
• 通讯作者: Li, Zhouyu

Principles and Practices for Application-Network Co-Design in Edge Computing

边缘计算应用网络协同设计的原则与实践

• DOI: 10.1109/mnet.128.2200430
• 发表时间: 2022
• 期刊: IEEE Network
• 影响因子: 9.3
• 作者: Yu, Ruozhou;Xue, Guoliang
• 通讯作者: Xue, Guoliang

Data-Driven Edge Resource Provisioning for Inter-Dependent Microservices with Dynamic Load

• DOI: 10.1109/globecom46510.2021.9685155
• 发表时间: 2021-12
• 期刊: 2021 IEEE Global Communications Conference (GLOBECOM)
• 作者: Ruozhou Yu;Szu-Yu Lo;Fangtong Zhou;G. Xue

FedAegis: Edge-Based Byzantine-Robust Federated Learning for Heterogeneous Data

• DOI: 10.1109/globecom48099.2022.10000981
• 发表时间: 2022-12
• 期刊: GLOBECOM 2022 - 2022 IEEE Global Communications Conference
• 作者: Fangtong Zhou;Ruozhou Yu;Zhouyu Li;Huayue Gu;Xiaojian Wang

Edge-Assisted Collaborative Perception in Autonomous Driving: A Reflection on Communication Design

自动驾驶中的边缘辅助协作感知：对通信设计的反思

• DOI: 10.1145/3453142.3491413
• 发表时间: 2021
• 期刊: ACM/IEEE Symposium on Edge Computing (SEC
• 作者: Yu, Ruozhou;Yang, Dejun;Zhang, Hao
• 通讯作者: Zhang, Hao