Estimating Probabilistic Safe WCET Ranges of Real-Time Systems at Design Stages

TL;DR

This paper presents an automated method to estimate probabilistic safe WCET ranges in early design stages of real-time systems, combining search algorithms and logistic regression to ensure deadline compliance with high confidence.

Contribution

It introduces a novel approach that integrates search algorithms with logistic regression to determine probabilistic safe WCET ranges early in system design.

Findings

Efficiently estimates probabilistic safe WCET ranges for industrial systems.

Accurately predicts deadline satisfaction with high confidence.

Applicable across multiple domains and synthetic systems.

Abstract

Estimating worst-case execution times (WCET) is an important activity at early design stages of real-time systems. Based on WCET estimates, engineers make design and implementation decisions to ensure that task executions always complete before their specified deadlines. However, in practice, engineers often cannot provide precise point WCET estimates and prefer to provide plausible WCET ranges. Given a set of real-time tasks with such ranges, we provide an automated technique to determine for what WCET values the system is likely to meet its deadlines, and hence operate safely with a probabilistic guarantee. Our approach combines a search algorithm for generating worst-case scheduling scenarios with polynomial logistic regression for inferring probabilistic safe WCET ranges. We evaluated our approach by applying it to three industrial systems from different domains and several synthetic systems. Our approach efficiently and accurately estimates probabilistic safe WCET ranges within which deadlines are likely to be satisfied with a high degree of confidence.