A Hierarchical Tree-Based Syslog Clustering Scheme for Network Diagnosis

S. Rao, Minghui Wang, Cuixia Tian, Xin’an Yang, Xiang Ao
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引用次数: 2

Abstract

With the continuous development of Information Technology, modern networks have been widely utilised. Since the complex network structure causes growing difficulties in maintenance, log analysis has been widely studied in recent years for network diagnosis. System log clustering is mainly focused for root cause analysis. In this paper, a hierarchical tree-based clustering scheme is proposed that could accurately group system logs according to both time and network constraints without any training and parameter settings. Furthermore, it largely accelerates the matching process by reducing matching times and significantly boosts the performance of hit rate (100%) and match efficiency (16%) comparing to other clustering strategies, which greatly helps with precise network diagnosis.
一种基于层次树的网络诊断Syslog日志聚类方案
随着信息技术的不断发展,现代网络得到了广泛的应用。由于复杂的网络结构给维护带来越来越大的困难,日志分析在网络诊断中得到了广泛的研究。系统日志聚类主要用于根本原因分析。本文提出了一种基于分层树的聚类方案,该方案可以在不进行任何训练和参数设置的情况下,根据时间和网络约束对系统日志进行准确的分组。通过减少匹配次数,极大地加快了匹配过程,与其他聚类策略相比,命中率(100%)和匹配效率(16%)显著提高,对精确的网络诊断有很大帮助。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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