Breaking Down Sources of Dynamic Time Error for Chains of Networked Devices using Monte Carlo Analysis

Abstract

Monte Carlo analysis of Dynamic Time Error across long chains (e.g. 100 hops) of networked devices offers useful advantages compared to time series simulation. The former is not a replacement for the latter, but runtimes are orders of magnitude shorter allowing faster iteration when optimizing configuration parameters, and the approach allows for deep insights into the source of errors and how they accumulate. A combination of Monte Carlo analysis and Time Series simulation is more powerful than either on its own.This paper describes the Monte Carlo analysis approach developed during work in the IEC/IEEE 60802 group; some of the insights into how Clock Drift and Timestamp Errors generate Dynamic Time Errors and how those errors accumulate; and the applicability of both beyond the group’s focus on industrial automation.