Integer programming techniques for static scheduling of hard real-time systems

Abstract

Hard real-time systems focus on obtaining a feasible schedule while satisfying different temporal requirements. In safety-critical applications, this schedule is generated offline. This article explores different integer linear programming techniques (ILP) to schedule uniprocessor hard real-time systems. The goal is to efficiently obtain a static schedule for periodic tasks and partitioned systems where temporal and spatial isolation is crucial. The advantage of the proposed ILP techniques is the possibility of choosing the optimization criteria so that deadlines are met and better performance quality is achieved. The drawback is the time spent finding an optimal solution. We propose an ILP method that reduces by 70% the time needed to obtain an optimal solution compared to basic approaches. This method is called the rolling task MILP approach and the optimization problem is addressed task by task. Experimental results show that our approach also achieves better results than heuristics when trying to reduce temporal parameters such as response times, context switches, and jitter. This makes our solution suitable for control systems and other applications.