Minimum Delay Optimization for Message Scheduling in In-Vehicle Applications Based on Pheromone Resetting Strategy
Junqiang Jiang, Lunxin Xie, Duqun Zhou, Bo Fan · 2022
In-vehicle applications generally have latency requirements; serious safety accidents will likely be caused due to the applications failing to take the correct actions within a specified time frame. In this study, a Pheromone Resetting Ant Colony Optimization (PRACO) algorithm is proposed to address the calculation of the minimum response time of an application whose messages are transmitted by using the Controller Area Network with flexible data rates (CAN FD) bus. A Random Popup (RP) algorithm is equipped in PRACO to quickly obtain the valid message sequence, followed by resetting the pheromones on all paths if ants find a new optimal valid message sequence path. The minimum response delay of an in-vehicle application can be further got through a continuous iterative search and pheromone update. A Directed Acyclic Graph (DAG) workflow scheduling example and an Adaptive Cruise Control (ACC) application are used to conduct the simulation experiment. The results show that our PRACO algorithm significantly outperforms other static scheduling algorithms in obtaining the lowest response latency.