CRII: CNS: Towards an Efficient Serverless Mobile Edge Computing Network

CRII：CNS：迈向高效的无服务器移动边缘计算网络

• 批准号: 2153220
• 负责人: Xingyu Zhou
• 金额: $ 17.5万
• 依托单位: Wayne State University
• 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=2153220&HistoricalAwards=false
• 关键词: CRII; CNS; Towards; Efficient; Serverless

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).Serverless computing has emerged as an event-driven cloud computing paradigm that enjoys many advantages over traditional cloud computing. This includes automated server management, pay-as-you-use pricing, and massive parallelism, all of which make it an attractive approach for mobile edge computing (MEC). However, both the resource-constrained nature of edge nodes and the latency-sensitive nature of bursty workloads in MEC result in fundamental challenges to fulfilling the promise of serverless computing in MEC networks from the perspectives of both service providers and application developers. To unleash the full potential of serverless mobile edge computing, this project is organized around three interrelated tasks: (i) the development of locality-aware load balancing schemes for serverless requests that guarantee an optimal response time, (ii) the development of cost-effective, latency-driven resource configuration schemes, and (iii) the development of principles and techniques that allow application developers to utilize the great potential of parallelism offered by serverless computing. This project will lead to important societal and educational impacts. MEC has enabled a range of Internet of Things (IoT) applications across many areas, including security and surveillance, healthcare, industrial manufacturing, agriculture, and others. An efficient serverless mobile edge computing network will directly impact these applications, and ultimately, society at large. Moreover, the developed algorithms in this project will be a direct add-on for existing serverless computing platforms, and our proposed parallelism-assisted online learning approach will be a benchmark for the community when dealing with parallel computing-based machine learning edge applications. From an education perspective, this project will develop a curriculum that will be broadly shared, as well as train undergraduate and graduate students, while broadening participation in computing and engineering.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.

该奖项是根据2021年《美国救援计划法》的全部或部分资助的（公共法117-2）。《无人计算》已成为事件驱动的云计算范式，比传统的云计算具有许多优势。这包括自动服务器管理，付费使用定价和大量并行性，所有这些都使其成为移动边缘计算（MEC）的有吸引力的方法。但是，Edge节点的资源受限性质和MEC中爆发工作负载的潜伏敏感性都导致了从服务提供商和应用程序开发人员的角度实现MEC网络中无服务器计算的承诺的根本挑战。为了释放无服务器移动边缘计算的全部潜力，该项目围绕三个相互关联的任务进行组织：（i）开发当地意识到的负载平衡方案，以保证无线服务的响应时间，（ii）开发具有成本效益的，延迟驱动的资源配置方案的无效，以及（III）允许使用的范围的不允许使用的效率来源的技术，以实现III的开发。计算。该项目将导致重要的社会和教育影响。 MEC启用了许多领域的物联网（IoT）应用程序，包括安全和监视，医疗保健，工业制造，农业等。有效的无服务器移动边缘计算网络将直接影响这些应用程序，并最终影响整个社会。此外，该项目中开发的算法将是现有无服务器计算平台的直接附加组件，而我们提出的并行性辅助在线学习方法将在处理基于并行计算的机器学习边缘应用程序时成为社区的基准。从教育的角度来看，该项目将开发一项课程，该课程将广泛共享，并培训本科生和研究生，同时扩大了计算和工程的参与。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评估审查审查的审查标准来通过评估来通过评估来提供支持的。

项目成果

Differentially Private Linear Bandits with Partial Distributed Feedback

• DOI: 10.23919/wiopt56218.2022.9930524
• 发表时间: 2022-07
• 期刊: 2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt)
• 作者: Fengjiao Li;Xingyu Zhou;Bo Ji

On Kernelized Multi-Armed Bandits with Constraints

• DOI: 10.48550/arxiv.2203.15589
• 发表时间: 2022-03
• 期刊: ArXiv
• 作者: Xingyu Zhou;Bo Ji

(Private) Kernelized Bandits with Distributed Biased Feedback

具有分布式偏差反馈的（私人）内核化强盗

• DOI: 10.1145/3579318
• 发表时间: 2023
• 期刊: Proceedings of the ACM on Measurement and Analysis of Computing Systems
• 作者: Li, Fengjiao;Zhou, Xingyu;Ji, Bo
• 通讯作者: Ji, Bo

Interference Constrained Beam Alignment for Time-Varying Channels via Kernelized Bandits

通过核化强盗对时变通道进行干扰约束光束对准

• DOI: 10.48550/arxiv.2207.00908
• 发表时间: 2022
• 期刊: Proceedings of the International Symposium on Modeling and Optimization in Mobile Ad Hoc and Wireless Networks
• 作者: Deng, Yuntian;Zhou, Xingyu;Ghosh Arnob;Gupta, Abhishek;Shroff, Ness
• 通讯作者: Shroff, Ness