A Statistical Approach to Response-Time Analysis of Complex Real-Time Embedded Systems

Abstract

This paper presents RapidRT, a novel statistical approach to Worst-Case Response-Time (WCRT) analysis targeting complex embedded real-time systems. The proposed algorithm combines Extreme Value Theory (EVT) and other statistical methods in order to produce a probabilistic WCRT estimate. This estimate is calculated using response time data from either Monte Carlo simulations of a detailed model of the system, or from response-time measurements of the real system. The method could be considered as a pragmatic approach intended for complex industrial systems with real-time requirements. The target systems contain tasks with many intricate dependencies in theirtemporal behavior, which violates the assumptions of traditional analytical methods for response time analysis and thereby makes them overly pessimistic. An evaluation ispresented using two simulation models, inspired by an industrial robotic control system, and five other methods as reference.