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International Journal of Advance Scientific Research SCIENTIFIC IDEAS. INTERNATIONAL PERSPECTIVES.
ISSN 2750-1396 12 issues per year · Monthly
Crossref DOI: 10.37547/ijasr
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Articles Published:

Conceptual Architecture of Automated Inventory and Topological Modeling in Chaotic Multi-Vendor Networks

Vol. 6 No. 03 (2026): Volume 06 Issue 03 Pages 44-58
Authors
  • Qalandarov Jamil Jalolovich
    System Administrator, Digital Infrastructure Development Center, TATU named after Muhammad al-Khwarizmi, Uzbekistan
  • Omonov Zokir Hojiboy o'g'li
    Network Administrator, Digital Infrastructure Development Center, TATU named after Muhammad al-Khwarizmi, Uzbekistan
  • Akmalov Elyor Ilxomovich
    IT Developer, Director of Active Service LLC, Uzbekistan
DOI 10.37547/ijasr-06-03-06 ↗
RESEARCH OVERVIEW

Abstract

Modern enterprise networks are complex heterogeneous systems comprising equipment from various vendors (HPE, Huawei, SNR, Fortinet, Ubiquiti). This paper proposes and validates a conceptual architecture for automated device inventory and topological modeling in chaotic multi-vendor LANs. The network topology is modeled using Graph Theory (G=(V,E,W)), SNMP/LLDP data is automatically normalized, and identification is optimized using Go microservices. Real-world testing across a ~1000 IP enterprise network demonstrated that the system fully inventoried 67 management devices and 1600+ endpoints in 10 minutes and 19 seconds. A two-phase scanning approach (ICMP Discovery + Deep Scan) yielded a 4.3x overall speedup over sequential methods (44x speedup in initial discovery). Furthermore, automated trunk-port filtering of virtual machines resulted in a 91.4% precision rate in detecting unauthorized Shadow IT devices. Experimental validation confirmed significant structural advantages over traditional NMS platforms (Zabbix), serving as a robust foundation for future Software-Defined Networking (SDN) and AI/ML-based monitoring models.

Keywords

  • Automated inventory
  • Multi-vendor networks
  • Graph Theory
SOURCES & CITATIONS

References

1. Kurose, J. F., & Ross, K. W. (2017). Computer Networking: A Top-Down Approach (7th ed.). Pearson.
2. Harrington, D., Presuhn, R., & Wijnen, B. (2002). An Architecture for Describing Simple Network Management Protocol (SNMP) Management Frameworks. RFC 3411, Internet Engineering Task Force.
3. Congdon, P., et al. (2002). IEEE 802.1AB Station and Media Access Control Connectivity Discovery (LLDP). IEEE Standards Association.
4. Sivaraman, V., Gharakheili, H. H., Vishwanath, A., Boreli, R., & Mehani, O. (2015). Network-Level Security and Privacy Control for Smart-Home IoT Devices. IEEE 11th International Conference on Wireless and Mobile Computing (WiMob), 163–167.
5. Mauro, D. R., & Schmidt, K. J. (2005). Essential SNMP (2nd ed.). O'Reilly Media.
6. Clemm, A. (2006). Network Management Fundamentals. Cisco Press.
7. Diestel, R. (2017). Graph Theory (5th ed.). Springer-Verlag.
8. Sequeira, A. (2019). CCNP and CCIE Enterprise Core ENCOR 350-401 Official Cert Guide. Cisco Press.
9. Donovan, A., & Kernighan, B. W. (2015). The Go Programming Language. Addison-Wesley Professional.
10. InfluxData. (2023). InfluxDB Documentation: Time Series Database. https://docs.influxdata.com/
11. Boutaba, R., et al. (2018). A Comprehensive Survey on Machine Learning for Networking. Journal of Internet Services and Applications, 9(1), 1–99.
12. State Standards (O'z DSt) on information security and corporate network protection in the Republic of Uzbekistan.
13. Gartner. (2020). Shadow IT: How to Take Control. Gartner Research Report.
14. Kreutz, D., et al. (2015). Software-Defined Networking: A Comprehensive Survey. Proceedings of the IEEE, 103(1), 14–76.
15. Tanenbaum, A. S., & Wetherall, D. J. (2011). Computer Networks (5th ed.). Pearson Prentice Hall.
16. IEEE 802.1D-2004. IEEE Standard for Local and Metropolitan Area Networks: Media Access Control (MAC) Bridges. IEEE Standards Association.
17. McKeown, N., et al. (2008). OpenFlow: Enabling Innovation in Campus Networks. ACM SIGCOMM Computer Communication Review, 38(2), 69–74.
18. Flauzac, O., et al. (2015). SDN Based Architecture for IoT and Improvement of the Security. IEEE INCoS, 688–693.
19. Lyon, G. F. (2009). Nmap Network Scanning. Insecure.com LLC.
20. Mell, P., & Grance, T. (2011). The NIST Definition of Cloud Computing. NIST SP 800-145.
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