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Independent Tasks Scheduling using Parallel PSO in Multiprocessor Systems

机译:在多处理器系统中使用并行PSO进行独立任务调度

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Multiprocessor system often aims to minimize the schedule length of the submitted jobs. For this, efficient scheduling of the parallel tasks on multiprocessor system is required. As the scheduling is an NP-Hardproblem, meta-heuristics are often applied for this. This work applies parallel particle swarm optimization technique for multiprocessor task scheduling. As the scheduler designed using parallel PSO itself can execute in parallel on the multiprocessor systems the convergence is faster. The proposed algorithm takes care of local as well as global convergence. The performance evaluation of the proposed model is done by simulation and the result is quite encouraging.
机译:多处理器系统通常旨在最小化已提交作业的调度长度。为此,需要在多处理器系统上高效地调度并行任务。由于调度是一个NP-Hard问题,因此常将元启发法应用于此。这项工作将并行粒子群优化技术应用于多处理器任务调度。由于使用并行PSO本身设计的调度程序可以在多处理器系统上并行执行,因此收敛速度更快。该算法兼顾了局部收敛和全局收敛。通过仿真对提出的模型进行性能评估,结果令人鼓舞。

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