Abstract
We present DiPerF, a DIstributed PERformance evaluation Framework, aimed at simplifying and automating performance evaluation of networked services. DiPerF coordinates a pool of machines that access a target service and collect performance measurements, aggregates these measurements, and generates performance statistics. The aggregate data collected provide information on service throughput, service response time, service ‘fairness’ when serving multiple clients concurrently, and on the impact of network connectivity on service performance. We have used DiPerF in various environments (PlanetLab, Grid3, TeraGrid, and a cluster) and with a large number of services. This paper provides data that demonstrates that DiPerF is accurate: The aggregate client view matches the tested service view within a few percents, and scalable: DiPerF can handle more than 10,000 clients and 100,000 transactions per second. Moreover, rapid adoption and extensive use demonstrate that the ability to automate performance characteristics extraction makes DiPerF a valuable tool.
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