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中一个持久且日益普遍的挑战--故障-慢速容错。大多数现有的容错分布式系统的开发和测试都是为了容忍节点完全停止的故障，但它们通常不能很好地处理“慢故障”故障，即故障节点没有崩溃，而是以远低于标准性能的降级速度运行。故障缓慢故障可能由于各种原因而发生，包括硬件(例如，过热的芯片)、软件(例如，进程耗尽所有内存)、网络(例如，松动的电缆)和人为错误(例如，管理员在同一节点上启动太多进程)。在当前的许多容错分布式系统中，慢故障节点会阻碍健康节点的执行，从而损害整个系统的性能。例如，健康的节点可能会一直将出站消息缓冲到速度较慢的节点，直到它耗尽内存并崩溃。提高慢故障容错性是一个重要的问题，因为据报道，在部署在现代数据中心的大规模分布式系统中，慢故障是常见的。它们导致的性能问题更加隐蔽，也更难调试。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。由于分布式系统是云计算、集群和数据中心技术以及高性能计算等现代计算基础设施的基石，因此这项研究可能会对行业和社会产生重大影响。特别是，这项工作将与广泛使用的分布式数据库合作完成，特别是MongoDB和TiDB。PI们设想这一努力将成为石溪大学和伊利诺伊大学关于分布式系统技术的多学科研究和教育的催化剂。PI将以这项工作为核心，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学生人数都出现了前所未有的激增。PIS正在与司法部合作，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。督导人员会把这项建议的主题纳入他们所教授的课程。私人投资机构长期致力于本科教育和研究，并扩大对代表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加入他们的研究小组。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.