Abstract

Traditional real-time systems are designed using preemptive scheduling and worst-case execution time estimates to guarantee the execution of high priority tasks. There is, however, an interest in exploring non-preemptive scheduling models for real-time systems, particularly for soft real-time multimedia applications. In this paper we propose a new algorithm that uses multiple scheduling strategies. Our goal in this research is to improve the success rate of the well-known Earliest Deadline First (EDF) approach even when the load on the system is very high. Our approach, known as group-EDF (gEDF) is based on (dynamic) grouping of tasks with deadlines that are very close to each other, and using Shortest Job First (SJF) technique to schedule tasks within the group. We will present results comparing gEDF and EDF using randomly generated tasks with varying execution times, release times, deadlines and tolerance to missing deadlines, under varying workloads. We believe that the grouping of tasks with similar deadlines and utilizing information other than deadlines (such as execution times, priorities or resource availability) for scheduling tasks within a group can lead to new and more efficient real-time scheduling algorithms