Abstract
Most of the multiprocessor real-time scheduling algorithms follow the partitioned approach, the global approach, or the semipartitioned approach which is a hybrid of the first two by allowing a small subset of tasks to migrate. EDF-fm (Earliest Deadline First-based Fixed and Migrating) and EDF-os (Earliest Deadline First-based Optimal Semipartitioned) are semipartitioned approaches and were proposed for soft real-time sporadic task systems. Despite their desirable property that migrations are boundary-limited such as they can only occur at job boundaries, EDF-fm and EDF-os are not always optimal and have higher tardiness and cost of overheads due to task migration. To address these issues, in this paper, we classify the systems into different types according to the utilization of their tasks and propose a new semipartitioned scheduling algorithm, earliest deadline first-adaptive, dubbed as EDF-adaptive. Our experiments show that EDF-adaptive can achieve better performance than EDF-fm and EDF-os, in terms of system utilization and tardiness overhead. It is also proved that EDF-adaptive is able to lessen the task migration overhead, by reducing the number of migrating jobs and the number of processors to which a task is migrated.
Highlights
The partitioned and global approaches are the classical scheduling algorithms for real-time multiprocessor systems
Since our proposed approach in this paper concerns more on the latter, here, we focus on our review on semipartitioned schedulers, both for hard real-time (HRT) and soft real-time (SRT) systems
Proposed for periodic task systems, EKG (Earliest Deadline First with task splitting and K processors in a Group) [17] is HRT-optimal when a configurable parameter is reduced in a way that increases preemption frequency
Summary
The partitioned and global approaches are the classical scheduling algorithms for real-time multiprocessor systems Because the former assigns tasks statically to processors and does not allow the tasks to migrate, it cannot achieve higher system utilization whereas the latter schedules tasks from a single run queue and the task can be migrated [1]. Semipartitioned scheduling extends the partitioned scheduling by allowing a (usually small) subset of tasks to migrate, and these tasks cannot be feasibly assigned to two or more processors by a partitioned scheduling algorithm [23,24,25,26] This type of approach is different from the global ones as the former use push migrations which are planned before execution whereas the latter use pull migrations which are reactive in nature and more difficult to account for and implement efficiently.
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