Evolutionary Algorithm for Incremental Scheduling in Systems of Systems with Real-Time Requirements

Abstract

Time-triggered Systems-of-Systems (SoS) promise to satisfy the real-time and dependability requirements of safety-relevant applications such as medical systems, smart manufacturing and defense systems. However, the time-triggered scheduling algorithms in the state-of-the-art were developed for monolithic systems and they do not support the requirements and constraints of SoS. Scheduling tasks and optimizing the resource allocation in SoS is more complex than in monolithic systems due to the autonomy of its constituting systems, the lack of central control, and no global information about the resources in different constituent systems.In this article, we propose a two-level interactive heuristic approach using a Genetic Algorithm (GA) to schedule real-time applications incrementally by adding them to the time-triggered SoS. We compute and deploy the schedule for each new SoS application at runtime after its arrival. Therefore, the limited communication and computational resources must be shared between different SoS applications released over time. By reducing the blocking time of shared resources, we can cope with the possible shortage of resources for future applications. Therefore, we develop a new resource allocation algorithm which creates more balance in the blocking times of shared resources and helps to satisfy future resource requests. We generate example scenarios to examine the schedulability of our new incremental scheduling algorithm. The experimental results show that the proposed optimization scheme compared to an incremental scheduler without blocking time considerations can find a better schedule for a sequence of applications.