At present, most of the scheduling models for real-time periodic tasks are established based on independent fixed periodic tasks and few by considering the task model with period allowed to change and the processor model in the scheduling process. In this paper, a task model and processor model based on line tree(LT) for sporadic real-time periodic tasks are designed, and a transformation algorithm from task line tree(TLT) model to processor line tree(PLT) model is proposed. The algorithm takes the least common multiple of all real-time periodic tasks as the benchmark of layer number, and based on the complete job replacement rule, the minimum common multiple of all real-time periodic tasks is used as the reference of layer number. In order to achieve the optimal multiprocessor scheduling result, the method of replacing the empty node of non-migrating job with the node of migrating job and the condition of allowing job to publish tasks ahead of time with variable cycle are used. Experimental results show that comparing with PEDF, GEDF and RMFF, the present method not only has higher core utilization and lower time loss rate, but also reduces the number of context switching and migration.
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.
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