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Cluster-based multiple task allocation in distributed computing system

机译:分布式计算系统中基于群的多任务分配

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Summary form only given. Most of the task allocation models & algorithms in distributed computing system (DCS) require a priori knowledge of its execution time on the processing nodes. Since the task assignment is not known in advance, this time is quite difficult to estimate. We propose a cluster-based dynamic allocation scheme, in a distributed computing system, which eliminate this time requirement. Further, as opposed to a single task allocation, generally proposed in most of the models, we consider multiple tasks. A fuzzy function is used for both the module clustering and processor clustering. Dynamic invocation of clustering and assignment is considered. Experimental results show the efficacy of the proposed model.
机译:摘要表格仅给出。分布式计算系统(DCS)中的大多数任务分配模型和算法需要在处理节点上的执行时间先验知识。由于任务分配预先知道,因此这次是很难估计的。我们提出了一种基于集群的动态分配方案,在分布式计算系统中消除了这一时间要求。此外,与单一任务分配相反,通常在大多数模型中提出,我们考虑多个任务。模糊功能用于模块群集和处理器群集。考虑了集群和分配的动态调用。实验结果表明了所提出的模型的功效。

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