期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2019
卷号：97
期号：7
页码：2076-2091
出版社：Journal of Theoretical and Applied
摘要：Cloud computing has received considerable interest from research institutions, developers, and individuals in the last years. A trace�s cluster of approximately 12,500 machines, referred to as the "Google cluster trace� had been initiated by Google. This paper examines the characteristics, download process and tools, and analysis of this trace dataset in an attempt to provide insights into a type of trace date similar to the date which is in the cloud environment. We analyzed trace dataset by using the K-means clustering algorithm executed over SQL Server to use the implemented methodology for enhancing cloud environment performance by allocating the data into clusters. This allocation was aimed to be used in distributing the upcoming tasks to the most suitable cluster, then to the most suitable machine which covers its need for resources. The clustering process generates some clusters depending on CUP rate for each task, these clusters represent the machines suitable to each range (Average) of CPU rate which is required from the upcoming task to be allocated. Depending on the relationship between tasks and machine data, machines could be selected of each produced cluster for calculating the availability of CPU usage. This calculation will be the millstone of future tasks allocation over cloud cluster machines depending on its resources availability and its suitability to future task resource requirements.
