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Performance Analysis and Mitigation of Virtual Machine Server by using Naive Bayes Classification

机译:使用Naive Bayes分类来虚拟机服务器的性能分析与缓解

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Evolution of virtualization in data center is fast and is being widely used in the world. Usage of virtual machine (VM) in data center (DC) cannot be aside from problems such as: Operating System (OS) problem, virtual network, memory and CPU utilizations. Besides of those problems, utilization of VM can be found in cloud computing technology to make more efficient and its performance should be good entirely. Problem in VM is very complex. It can be found in OS, application and physical server. To keep it in good performance, operational engineer should operate VM monitoring system in order to keep VM run well. This research will use several methods, such as: fuzzy Mamdani, holdout validation and naive Bayes. These methods will then create decision making for VM performance condition.
机译:数据中心虚拟化的演变是快速的,并且在世界上广泛使用。数据中心(DC)中的虚拟机(VM)的用法不能避免出现:操作系统(OS)问题,虚拟网络,内存和CPU利用率。除了那些问题之外,VM的利用可以在云计算技术中找到,以更高效,其性能应该完全良好。 VM中的问题非常复杂。它可以在OS,应用程序和物理服务器中找到。为了保持良好的性能,操作工程师应该操作VM监控系统,以便保持VM运行良好。本研究将使用多种方法,例如:模糊Mamdani,持有验证和天真贝叶斯。然后,这些方法将为VM性能条件创建决策。

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