Real-time Task Scheduling in Heterogeneous Multiprocessors System Using Hybrid Genetic Algorithm

Myungryun, Yoo
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Abstract

The real-time multiprocessor scheduling problem is one of the NP-hard problems. Furthermore, there are no papers which are concerned to heterogeneous multiprocessors system. This paper proposes a new real-time task scheduling algorithm using hGA (hybrid genetic algorithm) on heterogeneous multiprocessor environment. In solution algorithms, the GA (genetic algorithm) and the SA (simulated annealing) are cooperatively used. In this method, the convergence of GA is improved by introducing the probability of SA as the criterion for acceptance of new trial solution. The objective of proposed scheduling algorithm is to minimize total tardiness. The effectiveness of the proposed algorithm is shown through simulation studies. In simulation studies, the results of proposed algorithm show better than that of other algorithms.
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基于混合遗传算法的异构多处理器系统实时任务调度
实时多处理器调度问题是np困难问题之一。此外,对异构多处理机系统的研究还没有见过。提出了一种基于混合遗传算法的异构多处理机实时任务调度算法。在求解算法中,采用遗传算法(GA)和模拟退火算法(SA)协同求解。该方法通过引入SA的概率作为新试解接受的准则,提高了遗传算法的收敛性。提出的调度算法的目标是使总延迟最小化。仿真研究表明了该算法的有效性。在仿真研究中,所提算法的效果优于其他算法。
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