Optimization-based Resource Allocation for an Automotive Service-oriented Software Architecture
This paper presents an approach for allocation of resources in an automotive service-oriented software architecture. Using mathematical optimization, we assign computational resources of an automotive compute cluster to a set of software services. Additionally, scheduling parameters of services are optimized under the consideration of dependencies between data flows and computations within services. The optimization minimizes power consumption and the maximum execution times of critical effect chains in a multi-objective optimization problem. The evaluation investigates the achievable reduction in power consumption using an exemplary system. Furthermore, we demonstrate a sharp reduction in maximum execution times of effect chains that span multiple services and ECUs.