Allocating Software with Improved Resource Usage and Scheduling for Vehicle Control System Development

Allocating software components and messages to computing devices and their interconnecting networks is a great challenge in vehicle control system development. The allocation decisions are usually made at an early development stage without the implementation details of the computing platform. To produce low-cost products with correct vehicle control, the software allocation must facilitate the final system scheduling with better resource utilization and the presence of platform implementation uncertainties. In this paper, we present an allocation method to improve the resource utilization and scheduling while keeping the decisions independent of delayed platform implementation. Our method determines the allocation using a genetic algorithm with an optimization function combining the peak usage request and the usage request density to minimize the potential contentions on shared resources. The preliminary evaluation using the representative synthetic systems has shown the effectiveness and applicability of the method.