KPC-Toolbox: Simple Yet Effective Trace Fitting Using Markovian Arrival Processes

We present the KPC-Toolbox, a collection of Matlab scripts for fitting workload traces into Markovian Arrival Processes (MAPs) in an automatic way. We first present detailed sensitivity analysis that builds intuition on which trace descriptors are most important for queueing. This sensitivity analysis stresses the importance of matching higher-order correlations (i.e., joint moments) rather than higher order moments of the distribution and provides guidance on the relative importance of different descriptors on queueing. Given that the MAP parameterization space can be very large, we focus on first determining the order of the smallest MAP that can fit the trace well, using the Bayesian Information Criterion (BIC) for determining the best orderaccuracy trade-off. Having determined the order of the target MAP, the KPC-Toolbox automatically derives a MAP that captures accurately the most essential features of the trace. Extensive experimentation shows the effectiveness of the KPC-To...

• Type: Conference
• Year: 2008
• Where: QEST
• Authors: Giuliano Casale, Eddy Z. Zhang, Evgenia Smirni
• Keywords: Present Detailed Sensitivity, QEST 2008, Quantitative Evaluation Of Systems, Sensitivity Analysis, Trace Descriptors