基于跟踪的网络服务器行为分析

Nik Sultana, A. Rao, Zihao Jin, Pardis Pashakhanloo, Henry Zhu, V. Yegneswaran, B. T. Loo
{"title":"基于跟踪的网络服务器行为分析","authors":"Nik Sultana, A. Rao, Zihao Jin, Pardis Pashakhanloo, Henry Zhu, V. Yegneswaran, B. T. Loo","doi":"10.23919/CNSM46954.2019.9012750","DOIUrl":null,"url":null,"abstract":"Analysing software and networks can be done using established tools, such as debuggers and packet analysers, but using established tools to analyse network software is difficult and impractical because of the sheer detail the tools present and the performance overheads they typically impose. This makes it difficult to precisely diagnose performance anomalies in network software to identify their causes (is it a DoS attack or a bug?) and determine what needs to be fixed.We present Flowdar: a practical tool for analysing software traces to produce intuitive summaries of network software behaviour by abstracting unimportant details and demultiplexing traces into different sessions’ subtraces. Flowdar can use existing state-of-the-art tracing tools for lower overhead during trace gathering for offline analysis. Using Flowdar we can drill down when diagnosing performance anomalies without getting overwhelmed in detail or burdening the system being observed.We show that Flowdar can be applied to existing real-world software and can digest complex behaviour into an intuitive visualisation.","PeriodicalId":273818,"journal":{"name":"2019 15th International Conference on Network and Service Management (CNSM)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Trace-based Behaviour Analysis of Network Servers\",\"authors\":\"Nik Sultana, A. Rao, Zihao Jin, Pardis Pashakhanloo, Henry Zhu, V. Yegneswaran, B. T. Loo\",\"doi\":\"10.23919/CNSM46954.2019.9012750\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Analysing software and networks can be done using established tools, such as debuggers and packet analysers, but using established tools to analyse network software is difficult and impractical because of the sheer detail the tools present and the performance overheads they typically impose. This makes it difficult to precisely diagnose performance anomalies in network software to identify their causes (is it a DoS attack or a bug?) and determine what needs to be fixed.We present Flowdar: a practical tool for analysing software traces to produce intuitive summaries of network software behaviour by abstracting unimportant details and demultiplexing traces into different sessions’ subtraces. Flowdar can use existing state-of-the-art tracing tools for lower overhead during trace gathering for offline analysis. Using Flowdar we can drill down when diagnosing performance anomalies without getting overwhelmed in detail or burdening the system being observed.We show that Flowdar can be applied to existing real-world software and can digest complex behaviour into an intuitive visualisation.\",\"PeriodicalId\":273818,\"journal\":{\"name\":\"2019 15th International Conference on Network and Service Management (CNSM)\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 15th International Conference on Network and Service Management (CNSM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/CNSM46954.2019.9012750\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 15th International Conference on Network and Service Management (CNSM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/CNSM46954.2019.9012750","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

分析软件和网络可以使用现有的工具来完成,比如调试器和数据包分析器,但是使用现有的工具来分析网络软件是困难和不切实际的,因为这些工具提供了非常详细的细节,而且它们通常会带来性能开销。这使得精确诊断网络软件中的性能异常以确定其原因(是DoS攻击还是错误?)并确定需要修复的内容变得困难。我们提出Flowdar:一个实用的工具,用于分析软件痕迹,通过抽象不重要的细节和解复用痕迹到不同会话的子痕迹来产生网络软件行为的直观摘要。Flowdar可以使用现有的最先进的跟踪工具,在离线分析的跟踪收集过程中降低开销。使用Flowdar,我们可以在诊断性能异常时进行深入研究,而不会被细节淹没,也不会给观察到的系统增加负担。我们证明Flowdar可以应用于现有的现实世界软件,并可以将复杂的行为消化成直观的可视化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Trace-based Behaviour Analysis of Network Servers
Analysing software and networks can be done using established tools, such as debuggers and packet analysers, but using established tools to analyse network software is difficult and impractical because of the sheer detail the tools present and the performance overheads they typically impose. This makes it difficult to precisely diagnose performance anomalies in network software to identify their causes (is it a DoS attack or a bug?) and determine what needs to be fixed.We present Flowdar: a practical tool for analysing software traces to produce intuitive summaries of network software behaviour by abstracting unimportant details and demultiplexing traces into different sessions’ subtraces. Flowdar can use existing state-of-the-art tracing tools for lower overhead during trace gathering for offline analysis. Using Flowdar we can drill down when diagnosing performance anomalies without getting overwhelmed in detail or burdening the system being observed.We show that Flowdar can be applied to existing real-world software and can digest complex behaviour into an intuitive visualisation.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信