Uniprocessor Scheduling Strategies for Self-Suspending Task Systems

We study uniprocessor scheduling for hard real-time self-suspending task systems where each task may contain a single self-suspension interval. We focus on improving state-of-the-art fixed-relative-deadline (FRD) scheduling approaches, where an FRD scheduler assigns a separate relative deadline to each computation segment of a task. Then, FRD schedules different computation segments by using the earliest-deadline first (EDF) scheduling policy, based on the assigned deadlines for the computation segments. Our proposed algorithm, Shortest Execution Interval First Deadline Assignment (SEIFDA), greedily assigns the relative deadlines of the computation segments, starting with the task with the smallest execution interval length, i.e., the period minus the self-suspension time. We show that any reasonable deadline assignment under this strategy has a speedup factor of 3. Moreover, we present how to approximate the schedulability test and a generalized mixed integer linear programming (MILP) that can be formulated based on the tolerable loss in the schedulability test defined by the users. We show by both analysis and experiments that through designing smarter relative deadline assignment policies, the resulting FRD scheduling algorithms yield significantly better performance than existing schedulers for such task systems.