Collaborative Research: CNS Core: Small: A new framework for building fail-slow fault-tolerant distributed systems

合作研究：CNS Core：Small：构建慢速容错分布式系统的新框架

• 批准号: 2130560
• 负责人: Tianyin Xu
• 金额: $ 25万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2130560&HistoricalAwards=false
• 关键词: Collaborative; Research; CNS; Core; Small

This project targets a long-lasting and an increasingly pervasive challenge of distributed system design and implementation—fail-slow fault tolerance. Most existing fault-tolerant distributed systems are developed and tested to tolerate faults where a node has completely stopped, but they often do not perform well with the “fail-slow” faults, where a faulty node has not crashed but is operating at a degraded speed far below the standard performance. Fail-slow faults can happen for various reasons including hardware (e.g., an overheated chip), software (e.g., the process uses up all the memory), network (e.g., a loose cable), and human errors (e.g., the administrator launches too many processes on the same node). In many current fault-tolerant distributed systems, the fail-slow nodes can damage the entire system performance by holding up the healthy nodes in their execution. For example, a healthy node may keep buffering outbound messages to the slow nodes until it uses up its memory and crash. Improving fail-slow fault-tolerance is an important issue as fail-slow faults have been reported to be common in large-scale distributed systems deployed in modern data centers. The performance issues they cause are more hidden and hard to debug. To help improve this situation, this work will develop a set of novel, transformative technologies, including distributed-system programming support, design patterns, and runtime verification techniques, that will be encapsulated in a unified programming framework and will dramatically improve the performance and fault-tolerance of modern distributed systems.This research may have a major impact on industry and society, since distributed systems are the cornerstones of modern computing infrastructures such as cloud computing, cluster and datacenter technologies, and high performance computing. In particular, this work will be done in collaboration with widely used distributed databases, specifically MongoDB and TiDB. The PIs envision this effort as a catalyst for multidisciplinary research and education on distributed systems technologies at Stony Brook University and the University of Illinois. The PIs will use this work as a core that they hope will eventually grow to agglutinate other faculty of diverse expertise with interests in cloud computing, distributed systems, and software engineering technologies. Both universities are experiencing an unprecedented surge of students in Computer Science. The PIs are working with the department to broaden the course offerings with multidisciplinary courses in the general area of cloud computing, distributed systems, reliable systems, and software engineering. The PIs will incorporate the topics in this proposal in the courses they are teaching. The PIs have a long-standing commitment to undergraduate education and research, and to broaden participation to under-represented minorities. They will use this work to involve undergraduates and under-represented students in their research groups.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.

该项目的目标是分布式系统设计和实现中一个长期且日益普遍的挑战——慢速容错。 大多数现有的容错分布式系统都是为了容忍节点完全停止的故障而开发和测试的，但它们通常在“慢速故障”故障中表现不佳，即故障节点没有崩溃，但运行速度远低于标准性能。发生慢速故障的原因有多种，包括硬件（例如，芯片过热）、软件（例如，进程耗尽了所有内存）、网络（例如，电缆松动）和人为错误（例如，管理员在同一节点上启动了太多进程）。在当前的许多容错分布式系统中，故障慢速节点可能会阻碍健康节点的执行，从而损害整个系统的性能。例如，健康节点可能会继续缓冲发送到慢速节点的出站消息，直到耗尽内存并崩溃。提高故障慢速容错能力是一个重要问题，因为据报道，故障慢速故障在现代数据中心部署的大规模分布式系统中很常见。它们引起的性能问题更加隐蔽且难以调试。为了帮助改善这种情况，这项工作将开发一套新颖的、变革性的技术，包括分布式系统编程支持、设计模式和运行时验证技术，这些技术将被封装在统一的编程框架中，并将极大地提高现代分布式系统的性能和容错能力。这项研究可能会对工业和社会产生重大影响，因为分布式系统是云计算、集群等现代计算基础设施的基石。 和数据中心技术以及高性能计算。特别是，这项工作将与广泛使用的分布式数据库（特别是 MongoDB 和 TiDB）合作完成。 PI 预计这项工作将成为石溪大学和伊利诺伊大学分布式系统技术多学科研究和教育的催化剂。 PI 将使用这项工作作为核心，他们希望这项工作最终能够凝聚其他对云计算、分布式系统和软件工程技术感兴趣的具有不同专业知识的教师。两所大学的计算机科学专业学生数量都出现了前所未有的激增。 PI 正在与该部门合作，通过云计算、分布式系统、可靠系统和软件工程等领域的多学科课程来扩大课程设置。 PI 会将本提案中的主题纳入他们所教授的课程中。 PI 长期致力于本科教育和研究，并扩大代表性不足的少数群体的参与。他们将利用这项工作让本科生和代表性不足的学生参与到他们的研究小组中。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力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

Relational Debugging - Pinpointing Root Causes of Performance Problems

关系调试 - 查明性能问题的根本原因

• 发表时间: 2023
• 期刊: USENIX Symposium on Operating Systems Design and Implementation
• 作者: Xiang Ren;Sitao Wang;Zhuqi Jin;David Lion;Adrian Chiu;Tianyi Xu;Ding Yuan
• 通讯作者: Ding Yuan

Push-Button Reliability Testing for Cloud-Backed Applications with Rainmaker

• 发表时间: 2023
• 作者: Yinfang Chen;Xudong Sun;Suman Nath;Ze Yang;Tianyi Xu

Automatic Reliability Testing For Cluster Management Controllers

• 发表时间: 2022
• 作者: Xudong Sun;Wenqing Luo;Jiawei Tyler Gu;Aishwarya Ganesan;Ramnatthan Alagappan;Michael Gasch;Lalith Suresh;Tianyin Xu

Fail through the Cracks: Cross-System Interaction Failures in Modern Cloud Systems

• DOI: 10.1145/3552326.3587448
• 发表时间: 2023-05
• 期刊: Proceedings of the Eighteenth European Conference on Computer Systems
• 作者: Lilia Tang;Chaitanya Bhandari;Yongle Zhang;Anna Karanika;Shuyang Ji;Indranil Gupta;Tianyi Xu

DepFast: Orchestrating Code of Quorum Systems

DepFast：编排 Quorum 系统代码

• 发表时间: 2022
• 期刊: Proceedings of the 2022 USENIX Annual Technical Conference
• 作者: Luo, Xuhao;Shen, Weihai;Mu, Shuai;Xu, Tianyin
• 通讯作者: Xu, Tianyin