ITR: Feedback Control of Dynamic Computing Systems

软件系统已经变得越来越复杂，并且期望在宽的操作范围内提供服务。 为了满足服务目标，软件开发人员提供了许多调优参数，这些参数必须仔细设置，以便系统提供可接受的性能和功能。 充分地调整这些参数通常需要系统管理员进行大量的试错实验。 由于工作负载和操作条件不断变化，参数必须不断调整以提供良好的性能。本研究项目将在两个示例系统中应用反馈控制来自动化参数调整回路。 第一种是广域复杂文件系统，通过乐观并发控制提供可变的一致性和性能。 反馈将用于安排副本协调和数据迁移，以便为最终用户提供可接受的性能和一致性。 第二个系统是一个数据库引擎，它提供了大量需要考虑的调优参数。反馈控制将用于使数据库管理员能够管理其服务器系统日益增长的复杂性。从这两个例子和其他工作，一个框架的反馈控制ofdynamic计算系统将开始出现。 该框架将使未来的计算系统能够提供可靠和强大的操作和可预测的性能，而无需昂贵的维护和持续的手动调整。

Software systems have become increasingly complex, and are expected toprovide service over wide operating ranges. To meet service goals,software developers provide many tuning parameters that must beset carefully for the system to provide acceptable performance andfunctionality. Tuning these parameters adequately often requires extensivetrial-and-error experimentation by system administrators. As workloads andoperating conditions continually change, the parameters must be endlesslyre-tuned to provide good performance.This research project will apply feedback control to automate thisparameter tuning loop in two example systems. The first, a wide-areareplicated file system, provides variable consistency and performancethrough optimistic concurrency control. Feedback will be used to schedulereplica reconciliation and data migration to provide acceptableperformance and consistency to end users. The second system, a databaseengine, offers a large variety of tuning parameters to be considered.Feedback control will be used to enable database administrators to managethe growing complexity of their server systems. From these two examples and other work, a framework for feedback control ofdynamic computing systems will begin to emerge. This framework will enablefuture computing systems to offer reliable and robust operation andpredictable performance, without costly maintenance and continual manualtuning.