A comparative analysis of open source network monitoring tools

Ali Al Shidhani, Khalil Al Maawali, Dawood Al Abri, Hadj Bourdoucen

Research output: Contribution to journalArticle

Abstract

Nowadays, the heavy reliance on computer networks necessitates minimizing outage time, increasing the availability of services, and preventing network related problems. Such realization requires continuous monitoring and observation. This is not a trivial task. Thus, automatic network monitoring tools are deployed to monitor and analyze the traffic trespassing network devices. There is an increasing demand for automated network monitoring tools and selecting a suitable candidate can become a challenging task. Some computerized network monitoring tools and systems are available, including expensive proprietary/closed-source solutions and Free Open Source Software (FOSS) systems. Three of the most popular FOSS network monitoring systems are: Nagios, OpenNMS and Zabbix. They are solid competitors to the available proprietary solutions. This paper evaluates the strengths and weaknesses of these tools. A qualitative and quantitative evaluation of the tools were conducted through monitoring real-time network traffic. The paper presents a thorough comparison between the tools. The comparison results are vital for network administrators wishing to adopt the studied monitoring tools.

Original languageEnglish
Pages (from-to)1-19
Number of pages19
JournalInternational Journal of Open Source Software and Processes
Volume7
Issue number2
DOIs
Publication statusPublished - Apr 1 2016

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Monitoring
Computer networks
Outages
Computer systems
Availability
Open source software

Keywords

  • Computing Systems
  • FOSS
  • IP Networks
  • Network Management Systems
  • Network Monitoring
  • NMS
  • Open Source

ASJC Scopus subject areas

  • Software

Cite this

A comparative analysis of open source network monitoring tools. / Al Shidhani, Ali; Al Maawali, Khalil; Al Abri, Dawood; Bourdoucen, Hadj.

In: International Journal of Open Source Software and Processes, Vol. 7, No. 2, 01.04.2016, p. 1-19.

Research output: Contribution to journalArticle

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