| Popis: |
In order to better understand and describe tasks and improve the ability of Cloud, the analyzing of tasks is essential. A coarse-grained analysis, cluster analysis, and intra-cluster analysis are used to model tasks for the analysis of a one-month trace of a Google MapReduce cluster across about 12,000 machines. In this paper, we consider the k value which is central to the performance of k-means algorithm can effect on modeling. Besides, we also take the selection of attributes into account which are used as the dimension when tasks are classified. Experiment results by using different type of task attributes and k value show the well performance of our approach. |
