Approximation of Worst-Case Traversal Times in Real-Time Ethernet Networks: Exploring the Potential of Many-Objective Optimization for Simulation Aggregation

Simulation is an important tool for the verification of modern complex time-critical communication systems, especially when worst-case schedulability analysis is not available. Evaluating worst-case traversal times via simulation traditionally involves resource-intensive long simulations that are poorly parallelizable. Recent research has demonstrated that aggregating many short simulations with randomized starting conditions yields substantial improvements over this classical approach in terms of likelihood of observing very large communication latencies. In this study, we explore the potential of many-objective optimization to further enhance the efficiency of the aggregation approach.
To this end we further reduce the length of the aggregated simulations and perform many-objective optimization to set the starting conditions, namely the node start offsets and initial flow scheduling order. Our approach consists in modelling the approximation of worst-case traversal times as a many-objective Pareto optimization problem in the context of real-time Ethernet networks. Performance evaluation, conducted on different industrially relevant use cases from the automotive and aerospace domains, shows up to 46.42% increased end-to-end latencies for a 50 times shorter total simulation time, in comparison to the traditional approach of running single long simulations.