Optimal Scheduling of Time-Sensitive Networks for Automotive Ethernet Based on Genetic Algorithm

In this paper, we proposed a scheduling method to optimize a time-critical traffic using genetic algorithm in automotive ethernet networks. The proposed traffic scheduling method aims to generate a transmission schedule to minimize end-to-end delay, variation of reception time at the destination (jitter), and bandwidth utilization. These indicators should be simultaneously considered when generating a schedule since they are closely related to the performance of the networks. However, it is not easy to schedule the traffic considering these indicators together since they have different sizes and units. To solve this problem, the fitness function to evaluate performance of a chromosome has normalized indicators as parameters. A chromosome in the genetic algorithm consists of genes containing information (size, transmission period, and network delay) of messages to be scheduled. Finally, the applicability of the proposed schedule optimization method was examined by simulating an extended automotive Ethernet network for an autonomous vehicle.