Determining Model Accuracy of Network Traces
Almudena Konrad
Ben Y. Zhao
Anthony D. Joseph
Elsevier Journal of Computer and System
Sciences, Vol. 72, No. 7, November 2006, Pages 1156-1171
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Paper Abstract
Accurate network modeling is critical to the design of network protocols.
Traditional modeling approaches, such as Discrete Time Markov Chains (DTMC)
are limited in their ability to model time-varying characteristics. This
problem is exacerbated in the wireless domain, where fading events create
extreme burstiness of delays, losses, and errors on wireless links. In this
paper, we describe the data preconditioning modeling technique that is
capable of capturing the statistical characteristics of wired and wireless
network traces. We revise our previous developed data preconditioning
modeling algorithm, the Markov-based Trace Analysis (MTA), and present the
Multiple states MTA (MMTA)
algorithm. Our main contributions are methodologies
created to quantify the accuracy of network models, methodology to
choose the most accurate model for a given network
and characteristic of interest (e.g., delay, loss, or error
process), and the validation of our data preconditioning modeling algorithms.