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

这个项目的目标是分布式系统设计和实现的一个长期且日益普遍的挑战——慢故障容错。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时的故障而开发和测试的，但是它们通常在“故障缓慢”故障中表现不佳，即故障节点虽然没有崩溃，但其运行速度远远低于标准性能。慢速故障可能由于各种原因发生，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，故障缓慢节点会阻碍正常节点的执行，从而损害整个系统的性能。例如，运行正常的节点可能会将出站消息缓冲到运行缓慢的节点，直到耗尽内存并崩溃。由于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，因此提高慢速故障容错性是一个重要的问题。它们导致的性能问题更加隐蔽，而且难以调试。为了帮助改善这种情况，这项工作将开发一组新颖的、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一个统一的编程框架中，并将显著提高现代分布式系统的性能和容错性。这项研究可能会对工业和社会产生重大影响，因为分布式系统是现代计算基础设施（如云计算、集群和数据中心技术以及高性能计算）的基石。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。项目负责人认为，这项工作将促进石溪大学和伊利诺伊大学在分布式系统技术方面的多学科研究和教育。pi将把这项工作作为核心，他们希望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不同专业知识的教员。这两所大学的计算机科学专业的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一般领域的多学科课程来扩大课程范围。pi将在他们所教授的课程中纳入本提案中的主题。长期以来，ppi一直致力于本科教育和研究，并扩大代表性不足的少数民族的参与。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。

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.