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: 2130590
• 负责人: Shuai Mu
• 金额: $ 24.95万
• 依托单位: SUNY at Stony Brook
• 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=2130590&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.

该项目针对分布式系统设计和实施（Fail-Slow slow Farterance）的持久和越来越普遍的挑战。开发和测试了大多数现有的耐故障分布式系统，以耐受节点完全停止的故障，但是它们通常在“失败慢”故障的情况下表现不佳，因为故障节点尚未崩溃，但以降级速度远低于标准性能。出于各种原因，可能发生故障 - 慢性故障，包括硬件（例如，过热的芯片），软件（例如，该过程使用所有内存），网络（例如，宽松的电缆）和人体错误（例如，管理员在同一节点上启动了太多的进程）。在许多当前容忍故障的分布式系统中，失败的节点可以通过在执行中保持健康的节点来损害整个系统性能。例如，健康的节点可能会继续向慢节点缓冲出站消息，直到它消除其内存和崩溃为止。改善失败 - 慢性故障耐受性是一个重要的问题，因为据报道，在现代数据中心部署的大规模分布式系统中，故障 - 慢断层很常见。他们引起的性能问题更隐藏，难以调试。为了帮助改善这种情况，这项工作将开发一系列新型的变革性技术，包括分布式系统编程支持，设计模式和运行时验证技术，这些技术将封装在统一的编程框架中，并会极大地改善对现代分布式系统的绩效和竞争力，这些研究可能会对工业和社会产生重大影响，因为它可能会构成现代化的综合系统。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合作完成。 PIS设想了这项努力作为Stony Brook大学和伊利诺伊大学分布式系统技术的多学科研究和教育的催化剂。 PI将把这项工作用作核心，他们希望最终会发展起来，以融合了对云计算，分布式系统和软件工程技术的兴趣的其他潜水员专业知识的教师。两所大学都经历了计算机科学领域的前所未有的学生。 PI与部门合作，通过云计算，分布式系统，可靠系统和软件工程的多学科课程扩大课程产品。 PI将在他们正在教的课程中将主题纳入本提案中。 PI对本科教育和研究有一项长期的承诺，并将参与扩大到代表不足的少数民族。他们将使用这项工作将本科生和代表性不足的学生参与其研究小组。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响评估标准，通过评估诚实地表示支持。

项目成果

Rolis: a software approach to efficiently replicating multi-core transactions

• DOI: 10.1145/3492321.3519561
• 发表时间: 2022-03
• 期刊: Proceedings of the Seventeenth European Conference on Computer Systems
• 作者: Weihai Shen;Ansh Khanna;Sebastian Angel;S. Sen;Shuai Mu

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

NCC: Natural Concurrency Control for Strictly Serializable Datastores by Avoiding the Timestamp-Inversion Pitfall

• DOI: 10.48550/arxiv.2305.14270
• 发表时间: 2023-05
• 作者: Haonan Lu;Shuai Mu;S. Sen;Wyatt Lloyd

Waverunner: An Elegant Approach to Hardware Acceleration of State Machine Replication

Waverunner：状态机复制硬件加速的优雅方法

• 发表时间: 2023
• 期刊: The 20th USENIX Symposium on Networked Systems Design and Implementation (NSDI '23
• 作者: Alimadadi, Mohammadreza;Mai, Hieu;Cho, Shenghsun;Ferdman, Michael;Milder, Peter;Mu, Shuai
• 通讯作者: Mu, Shuai