Analysis of Enterprise Network Performance Using the SNMP (Simple Network Management Protocol) Method

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Abstract

This study examines the implementation of the Simple Network Management Protocol (SNMP) integrated with the Cacti monitoring platform to evaluate enterprise network performance within a simulated environment using PNETLab. A quantitative approach was applied through continuous data collection and measurement of key performance indicators such as throughput, packet loss, delay, and availability. The experiment utilized virtual Mikrotik routers connected to an Ubuntu-based Cacti server configured for SNMP polling and RRDTool data storage. Real-time visualization enabled efficient tracking of network behavior and early detection of anomalies. The results showed that under normal conditions, the network achieved stable performance with throughput between 70–90% of link capacity, zero packet loss, latency below 150 milliseconds, and availability above 99%, meeting ITU-T/TIPHON Quality of Service (QoS) standards. When faults were simulated, the system accurately detected and displayed traffic interruptions, allowing rapid identification and resolution of network issues. Compared with other monitoring tools such as Zabbix and Nagios, the SNMP–Cacti integration proved simpler to configure while maintaining analytical precision and reliability. These findings confirm that Cacti, supported by SNMP, provides an efficient, scalable, and low-overhead solution for enterprise network monitoring. Future development may incorporate SNMPv3 for enhanced security and automated alert systems or predictive analytics to improve responsiveness and proactive maintenance in larger infrastructures.

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How to Cite

Alwanto, H., & Yel, M. B. (2025). Analysis of Enterprise Network Performance Using the SNMP (Simple Network Management Protocol) Method. Journal Innovations Computer Science, 4(2), 335-344. https://doi.org/10.56347/jics.v4i2.346

Article Details

  • Volume: 4
  • Issue: 2
  • Pages: 335-344
  • Published:
  • Section: Article
  • Copyright: 2025
  • ISSN: 2961-970X

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