An Intelligent Monitoring System For DMVPN-Based Network

Abstract

This paper presents the design, implementation, and evaluation of a secure, scalable, and intelligent monitoring framework for Dynamic Multipoint Virtual Private Network (DMVPN) deployments. The proposed architecture adopts a layered model in which a Wide Area Network serves as the underlay, while DMVPN Phase 3 with multipoint Generic Routing Encapsulation (mGRE) tunnels protected by IPsec and IKEv2 forms the secure overlay. Enhanced Interior Gateway Routing Protocol (EIGRP) is deployed for dynamic route discovery and optimized spoke-to-spoke communication. A Python-based monitoring engine, built on Netmiko, collects operational telemetry through read-only SSH sessions, normalizes it into JSON, and applies rule-based detection logic against a healthy baseline. The system operates with a ten-second polling interval and is integrated with a centralized dashboard that visualizes tunnel status, routing adjacencies, and security associations. Experimental validation in GNS3 demonstrates that tunnel and routing failures are detected within a single monitoring cycle, achieving an estimated improvement of approximately 95% in fault detection speed compared to traditional manual approaches. The framework consolidates distributed CLI-based verification into a unified, automation-ready interface, supporting proactive enterprise network supervision.