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Cluster analysis algorithm based on key data integration for cloud computing

机译:基于关键数据集成的聚类分析算法在云计算中的应用

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摘要

In order to improve scheduling efficiency and a kind of cloud task scheduling algorithm of improved fuzzy cluster has been proposed. Firstly, cloud task scheduling algorithm of improved fuzzy cluster has been introduced, which mainly uses fuzzy FCM algorithm to complete resource cluster to three resource sets including computing type, storage type and bandwidth type in the context of using parallel processing to ensure the efficiency. The resource of cluster set with the longest time in completion will be liberated from the busy schedule to improve the utilisation ratio of resources, ensure load balance, reduce execution costs and enhance customer satisfaction; secondly, tasks have been allocated to each cluster through Min-Min heuristic algorithm and the results have been adjusted according to set threshold to obtain the better scheduling results. The experimental results show that the proposed algorithm is superior to the traditional algorithm without cluster in terms of execution time.
机译:为了提高调度效率,提出了一种改进的模糊聚类的云任务调度算法。首先,介绍了改进的模糊聚类的云任务调度算法,该算法主要使用模糊FCM算法在并行处理的情况下,将资源聚类完整地划分为计算类型,存储类型和带宽类型三个资源集,以确保效率。从繁忙的调度中释放完成时间最长的群集集的资源,以提高资源利用率,确保负载平衡,降低执行成本并提高客户满意度;其次,通过Min-Min启发式算法将任务分配给每个集群,并根据设置的阈值对结果进行调整,以获得更好的调度结果。实验结果表明,该算法在执行时间上优于传统的无聚类算法。

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