Publication | Open Access
A High Performance Load Balance Strategy for Real-Time Multicore Systems
18
Citations
35
References
2014
Year
Cluster ComputingLoad Balancing (Computing)EngineeringEnergy EfficiencyReal-time System DesignComputer ArchitectureReal-time SystemSystems EngineeringParallel ComputingPower-aware ComputingLoad BalancingComputer EngineeringScheduling (Computing)Computer ScienceReal-time Multicore SystemsPower ConsumptionReal-time AlgorithmNovel Scheduling AlgorithmScheduling AnalysisEnergy ManagementEdge ComputingReal-time Multiprocessor SystemProcessor CoreReal-time SystemsParallel ProgrammingPower-efficient Computing
Finding ways to distribute workloads to each processor core and efficiently reduce power consumption is of vital importance, especially for real-time systems. In this paper, a novel scheduling algorithm is proposed for real-time multicore systems to balance the computation loads and save power. The developed algorithm simultaneously considers multiple criteria, a novel factor, and task deadline, and is called power and deadline-aware multicore scheduling (PDAMS). Experiment results show that the proposed algorithm can greatly reduce energy consumption by up to 54.2% and the deadline times missed, as compared to the other scheduling algorithms outlined in this paper.
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