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Application of hybrid meta-heuristic algorithm for assigning real-time tasks to heterogeneous processors

机译:混合元启发式算法在异构处理器实时任务分配中的应用

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Heterogeneous multiprocessor system has the capability for providing low cost and high performance. Nevertheless, in order to take advantage of computing power of heterogeneous system, it is essential to use an efficient scheduling algorithm for task allocation to the available processors. This research mainly focuses on the development of task assignment algorithm for heterogeneous multiprocessor system. Assigning real-time tasks in heterogeneous multiprocessor are in general a challenging problem and NP hard. In this paper, Hybrid Max-Min Ant colony optimization algorithm (H-MMAS) is proposed to solve the real-time task assignment problem in heterogeneous multiprocessor. The objective of the proposed algorithm is to get a feasible task assignment solution, and to optimize energy consumption of every feasible task assignment solution. The performance of the proposed H-MMAS algorithm has been tested for consistent and inconsistent heterogeneous multiprocessor systems. Experimental comparisons with existing Modified BPSO algorithm demonstrate the effectiveness of the proposed H-MMAS algorithm.
机译:异构多处理器系统具有提供低成本和高性能的能力。但是,为了利用异构系统的计算能力,必须使用有效的调度算法将任务分配给可用处理器。这项研究主要集中在异构多处理器系统任务分配算法的开发上。在异构多处理器中分配实时任务通常是一个具有挑战性的问题,并且是NP难题。为了解决异构多处理器中的实时任务分配问题,提出了混合最大最小蚁群算法(H-MMAS)。该算法的目的是获得可行的任务分配解决方案,并优化每种可行任务分配解决方案的能耗。已针对一致和不一致的异构多处理器系统测试了所提出的H-MMAS算法的性能。与现有的改进型BPSO算法的实验比较证明了所提出的H-MMAS算法的有效性。

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