Abstract: The reasonable configuration of computer systems can dramatically improve performance of applications.Taking an NFS storage system as a case study, this paper proposed a statistical analysis-based performance tuning approach for storage systems and it proceeds in two phases. In the first phase, we leveraged the analysis-of-variance method(ANOVA) to model the performance sensitivity and thus identified the critical system parameters that have a significant effect on performance of applications; and furthermore, based on the previous phase, we employed the response surface methodology (RSM) to fulfill the tuning analysis of the critical parameters in the second phase. Combining the foregoing two steps, we then presented the performance tuning algorithm, which is eventually used to figure out the optimal combination of critical system parameters. Finally, the experimental results demonstrated the effectiveness and fcasibility of our performance tuning approach through an extensive evaluation under various representative scenarios including Web, E-mail, Fileserver, Linux utilities, and micro-benchmarks.

Key words: Performance tuning, Analysis of variance, Response surface methodology, Storage system, Performance evalution