Collaborative Research: CNS Core: Small: Accelerating Serverless Cloud Network Performance

协作研究：CNS 核心：小型：加速无服务器云网络性能

• 批准号: 2229454
• 负责人: Yan Chen
• 金额: $ 30万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2229454&HistoricalAwards=false
• 关键词: Collaborative; Research; CNS; Core; Small

Serverless computing has revolutionized cloud programming and is poised to become the next dominant cloud computing paradigm. Among the major allures of serverless computing is “agile autoscaling”, which brings forth both efficiency and economic advantages. However, such flexibility is accompanied by new network performance challenges that are uniquely endemic to the serverless compute environments. For example: (1) internal function chain communication becomes a bottleneck for serverless applications and (2) a unified function gateway increases the number of indirect connections in function chains that further impairs network performance. This project proposes a cross-layered effort that seeks to optimize the function chain communication in severless-cloud environments by exploring multiple, synergistic strategies to reduce latency in function-chain communication. The proposed solution includes (1) a new QUIC-based network substrate that can simultaneously improve performance and security, without the need for tenant code modification and (2) use of data-plane programming and informed request prediction to optimize resource allocation and mitigate cold-start issues in serverless multi-tenant clouds. This work will empower a broad class of novel serverless applications with stringent latency and security requirements and our proposed designs will be universally applicable across popular cloud platforms. This project will make the proposed implementations open-source and publicly release our evaluation environments through the NSF Fabric testbed, thus benefiting diverse stakeholders. This project will actively explore the transition of our work to commercial cloud services and open-source serverless communities, such as OpenFaaS and the QUIC-go project. This project will incorporate a detailed education and outreach plan targeting undergraduate and graduate researchers (through courses and summer internships), and women and minorities (through organizations like ThriveWiSE).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.

无服务器计算已经彻底改变了云编程，并有望成为下一个占主导地位的云计算范式。无服务器计算的主要吸引力之一是“敏捷自扩展”，它带来了效率和经济优势。然而，这种灵活性伴随着新的网络性能挑战，这些挑战是无服务器计算环境特有的。例如：(1)内部功能链通信成为无服务器应用程序的瓶颈；(2)统一功能网关增加了功能链中间接连接的数量，进一步损害了网络性能。该项目提出了一项跨层工作，旨在通过探索多种协同策略来减少功能链通信中的延迟，从而优化多云环境中的功能链通信。提出的解决方案包括(1)一个新的基于quic的网络基板，它可以同时提高性能和安全性，而不需要修改租户代码；(2)使用数据平面编程和知情请求预测来优化资源分配并减轻无服务器多租户云中冷启动问题。这项工作将为具有严格延迟和安全要求的新型无服务器应用程序提供广泛的支持，我们提出的设计将普遍适用于流行的云平台。该项目将使提议的实现开源，并通过NSF Fabric测试平台公开发布我们的评估环境，从而使不同的利益相关者受益。该项目将积极探索我们的工作向商业云服务和开源无服务器社区（如OpenFaaS和QUIC-go项目）的过渡。该项目将包括针对本科生和研究生研究人员（通过课程和暑期实习）以及女性和少数族裔（通过ThriveWiSE等组织）的详细教育和推广计划。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值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

QFaaS: accelerating and securing serverless cloud networks with QUIC

• DOI: 10.1145/3542929.3563458
• 发表时间: 2022-11
• 期刊: Proceedings of the 13th Symposium on Cloud Computing
• 作者: Kaiyu Hou;Sen-Shou Lin;Yan Chen;V. Yegneswaran