Genetic Algorithm Based ARINC 664 Mixed Criticality Optimization Using Network Calculus

Abstract

ARINC 664 is an Ethernet based deterministic networking standard providing data transmission with bounded delays among avionics sub-systems. This paper presents a Genetic Algorithm (GA) based ARINC 664 network delay optimization using the network calculus (NC), where the GA is used to effectively search the mapping of Virtual Links (VLs) to priority levels using the extended priority scheme. While there are only two priority levels in the ARINC 664 standard, the extended priority concept increases the number of priority levels to improve the schedulability of VLs. For each possible assignment of the VLs to the priority levels, the NC analysis provides the worst-case delay results for all VLs. We define three different fitness functions aiming to minimize the maximum, the average, and the standard deviation of the worst-case VL delays, respectively. The results demonstrate that the extended priority concept improves the schedulability of VLs and the GA optimization approach can successfully achieve the desired objectives for the VL delays if the appropriate cost function is selected.