How to parameterize models with bursty workloads

Although recent advances in theory indicate that burstiness in the service time process can be handled effectively by queueing models (e.g., MAP queueing networks [2]), there is a lack of understanding and of practical results on how to perform model parameterization, especially when this model parameterization must be derived from limited coarse measurements as is often encountered in practice. We propose a new modeling methodology based on the index of dispersion of the service process at a server, which is inferred by observing the number of completions within the concatenated busy periods of that server. The index of dispersion together with other measurements that reflect the "estimated" mean and the 95th percentile of service times are used to derive a MAP process that captures well burstiness and variability of the true service process, despite inevitable inaccuracies that result from inexact measurements. Detailed experimentation on a TPC-W testbed where all measurem...

• Type: Journal
• Year: 2008
• Where: SIGMETRICS
• Authors: Giuliano Casale, Ningfang Mi, Ludmila Cherkasova, Evgenia Smirni
• Keywords: Hardware, Model Parameterization, Service Time, Service Time Process, SIGMETRICS 2008