Publication | Open Access
U-EDF: An Unfair But Optimal Multiprocessor Scheduling Algorithm for Sporadic Tasks
67
Citations
21
References
2012
Year
Unknown Venue
Mathematical ProgrammingEngineeringComputer ArchitectureOperations ResearchImplicit DeadlinesSystems EngineeringOptimal MultiprocessorParallel ComputingCombinatorial OptimizationJob SchedulerComputer EngineeringScheduling (Computing)Computer ScienceScheduling AnalysisScheduling ProblemEdge ComputingReal-time Multiprocessor SystemParallel ProgrammingReal-time SystemsSporadic Tasks
A multiprocessor scheduling algorithm named U-EDF, was presented in [1] for the scheduling of periodic tasks with implicit deadlines. It was claimed that U-EDF is optimal for periodic tasks (i.e., it can meet all deadlines of every schedulable task set) and extensive simulations showed a drastic improvement in the number of task preemptions and migrations in comparison to state-of-the-art optimal algorithms. However, there was no proof of its optimality and U-EDF was not designed to schedule sporadic tasks. In this work, we propose a generalization of U-EDF for the scheduling of sporadic tasks with implicit deadlines, and we prove its optimality. Contrarily to all other existing optimal multiprocessor scheduling algorithms for sporadic tasks, U-EDF is not based on the fairness property. Instead, it extends the main principles of EDF so that it achieves optimality while benefiting from a substantial reduction in the number of preemptions and migrations.
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