Agentic AI for IPoDWDM Network Lifecycle Automation: An MCP-Enabled Architecture

📅 2026-07-07
📈 Citations: 0
Influential: 0
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🤖 AI Summary
This work addresses the lack of end-to-end automation and autonomous control in current multi-vendor, multi-layer IP-over-DWDM (IPoDWDM) networks, which hinders efficient service lifecycle management. To overcome this limitation, the authors propose a distributed, vendor-agnostic multi-MCP architecture that uniquely integrates MCP with Agentic AI. By synergistically combining SDN-based control, GNPy optical-layer modeling, real-time optical telemetry, and closed-loop feedback mechanisms, the proposed framework enables cross-vendor, cross-layer autonomous intelligent control and end-to-end service automation. Experimental validation on a real-world IPoDWDM testbed demonstrates that the approach significantly enhances network operational efficiency and intelligence.
📝 Abstract
We present a distributed, vendor-agnostic multi-MCP architecture for SDN-based automation and autonomous control of multi-vendor, multi-layer IPoDWDM networks. The framework enables E2E service lifecycle automation, closed-loop cross-layer control using GNPy model and optical telemetry, and is experimentally validated on a IPoDWDM testbed.
Problem

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

IPoDWDM
network automation
multi-vendor
service lifecycle
cross-layer control
Innovation

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

Agentic AI
IPoDWDM
MCP architecture
closed-loop control
service lifecycle automation
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