Gathering and using time measurements in distributed systems

It is often necessary to measure time in distributed computer systems. For example, timestamps are used for measuring the intervals between events (like banking transactions). They are also used for ordering events, as in the generation of transaction logs and debug traces. Perhaps their most common use is in performance evaluation, capacity planning, and the detection of unpredicted delays or bottlenecks. Measuring and using time in a distributed environment presents some unique challenges. This thesis illuminates these problems and presents techniques for the proper measurement and use of time. The first challenge is the clocks themselves. Chapter 3 describes the tradeoff between keeping clocks synchronized and keeping them accurate. The inaccuracies of networked workstation clocks are examined, and two statistical techniques are described for collecting time measurements in spite of these insufficiencies. The second challenge is synchronization. There is often a need to order events occurring on several processors, and to measure the time intervals between those events. Chapter 4 is a workload characterization of message-passing in distributed applications. In the course of this work, a method for generating global event traces was developed to get a system-wide view of message traffic. The message traffic was found to have characteristics similar to those observed in network packet traffic. The third challenge is performance prediction. Programmers need tools to help them understand the interactions between components of a system, and to project the execution time of prospective designs and configurations. Also, operating systems need fast tools to aid scheduling decisions and adaptation of software. We present a technique called benchmark blending that combines the speed of analytic models with the flexibility of benchmarks. Benchmark blending weaves time measurements with modeling techniques to create analytic models that: (1) quickly and accurately predict execution time, (2) implicitly incorporate much of the underlying system complexity, and (3) provide programmers with the needed insight to build efficient applications. We conclude that time measurements are a necessary part of building and studying distributed systems. Their use presents some challenges. This thesis presents solutions for three of those challenges: clock instability, global event descriptions, and performance prediction.