改进的t-SNE在云虚拟机异常检测中的应用

IF 4.4 4区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Enterprise Information Systems Pub Date : 2021-10-26 DOI:10.1080/17517575.2021.1995784

Fu Zhuang, Guoyuan Lin, Huanye He, Yifan Zhang, Yonggang Li, Hao Gu

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引用次数: 1

摘要

摘要针对云虚拟机异常检测过程中计算时间长的问题，提出了一种适用于云的C-t-SNE算法。该算法根据不同的任务对虚拟机进行分类，根据云虚拟机的相关参数构建投影空间。在降维之前，根据云虚拟机与任务之间的关系，从每个云虚拟机中提取比较数据集。在降维过程中，所有云虚拟机都被比较数据集取代，以减少数据比较的次数和计算时间。

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Improved t-SNE in Anomaly Detection of Cloud Virtual Machine

ABSTRACT Aiming at high computation time in the process of cloud virtual machine anomaly detection, a C-t-SNE algorithm suitable for cloud is proposed. The algorithm classifies the virtual machines according to the different tasks, constructs the projection space according to the relevant parameters of the cloud virtual machines. Before dimensionality reduction, comparison datasets are extracted from each cloud virtual machine according to the relationship between the cloud virtual machine and the task. In the process of dimensionality reduction, all cloud virtual machines are replaced by comparison datasets, so as to reduce the number of data comparison and the calculation time.

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来源期刊

Enterprise Information Systems 工程技术-计算机：信息系统

CiteScore

11.00

自引率

6.80%

发文量

审稿时长

6 months

期刊介绍： Enterprise Information Systems (EIS) focusses on both the technical and applications aspects of EIS technology, and the complex and cross-disciplinary problems of enterprise integration that arise in integrating extended enterprises in a contemporary global supply chain environment. Techniques developed in mathematical science, computer science, manufacturing engineering, and operations management used in the design or operation of EIS will also be considered.