A Technique to Reduce Preemption Overhead in Real-Time Multiprocessor Task Scheduling

Partitioning and global scheduling are two approaches for scheduling real-time tasks in multiprocessor environments. Partitioning is the more favored approach, although it is sub-optimal. This is mainly due to the fact that popular uniprocessor real-time scheduling algorithms, such as EDF and RM, can be applied to the partitioning approach with low scheduling overhead. In recent years, much research has been done on global real-time multiprocessor scheduling algorithms based on the concept of “proportionate fairness”. Proportionate fair (Pfair) scheduling [5],[6] is the only known optimal algorithm for scheduling real-time tasks on multiprocessor. However, frequent preemptions caused by the small quantum length for providing optimal scheduling in the Pfair scheduling make it impractical. Deadline Fair Scheduling (DFS) [1] based on Pfair scheduling tried to reduce preemption-related overhead by means of extending quantum length and sharing a quantum among tasks. But extending quantum length causes a mis-estimation problem for eligibility of tasks and a non-work-conserving problem. In this paper, we propose the Enhanced Deadline Fair Scheduling (E-DFS) algorithm to reduce preemption-related overhead. We show that E-DFS allows us to decrease quantum length by reducing overhead and save wasted CPU time that is caused by preemption-related overhead and miss-estimation of eligibility.