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Collaborative Resource Constraint Scheduling with a Fractional Shared Resource

机译:使用分数共享资源调度的协同资源约束

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We consider a collaborative scheduling problem motivated by mining in remote off-grid areas. In our model, jobs are assigned to processors who each have their own machine for executing them. As each job needs a certain amount of a resource shared between the processors, a coordination mechanism between the processors is needed. We present a framework which collaboratively computes a schedule while exchanging only limited information between the processors and a central resource manager. Our computational experiments show that our negotiated approach outperforms a one-shot solution approach by a wide margin and produces fairer solutions than a centralised genetic algorithm that can make use of the private information of each processor. Depending on the number of processors, the solution quality found by the mechanism presented in this paper is competitive with or even better than that of the centralised genetic algorithm.
机译:我们考虑通过在远程离网区域采集的协作调度问题。在我们的模型中,作业分配给每个有自己机器来执行它们的处理器。由于每个作业需要在处理器之间共享一定量的资源,因此需要处理器之间的协调机制。我们提出了一个框架,该框架在处理器和中央资源管理器之间仅在交换有限的信息时协作计算时间表。我们的计算实验表明,我们的协商方法优于一个广泛的保证金,并产生比可以利用每个处理器的私人信息的集中遗传算法的更公平的解决方案。根据处理器的数量,本文呈现的机制发现的解决方案质量与集中遗传算法的机构竞争甚至更好。

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