MCP-Enabled Agentic AI for Autonomous IPoDWDM Network Lifecycle Automation

πŸ“… 2026-07-07
πŸ“ˆ Citations: 0
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πŸ€– AI Summary
This study addresses the lack of unified autonomous capabilities in IP over DWDM (IPoDWDM) networks operating in multi-vendor environments. To this end, it proposes an agent-based AI architecture driven by a Multi-layer Control Platform (MCP), marking the first application of agent technology to the full lifecycle management of IPoDWDM networks. The approach integrates GNPy-based optical-layer simulation, real-time telemetry, and closed-loop control mechanisms to enable automated coordination and self-optimization across vendors in end-to-end multilayer networks. Experimental validation on a real-world testbed demonstrates the feasibility and effectiveness of the proposed solution in dynamic service provisioning, self-healing upon failures, and cross-layer resource coordination, significantly enhancing the network’s level of autonomy.
πŸ“ Abstract
This demo presents an MCP-enabled agentic AI architecture for autonomous control of vendor-agnostic IPoDWDM networks. We demonstrate live end-to-end lifecycle multi-layer automation and closed-loop control using GNPy and telemetry, validated on a real testbed.
Problem

Research questions and friction points this paper is trying to address.

IPoDWDM
autonomous automation
network lifecycle
vendor-agnostic
multi-layer control
Innovation

Methods, ideas, or system contributions that make the work stand out.

MCP
Agentic AI
IPoDWDM
Autonomous Networking
Closed-loop Control
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