# Intelligent Routing as a Service (iRaaS)

arXiv: https://arxiv.org/abs/2407.05901 · HTML: https://mlsanity.com/paper/2407.05901/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Jul 2024.

## Built on by (most cited first, 1 of 1)

- [Performance Comparison of IBN orchestration using LLM and SLMs](https://mlsanity.com/paper/2603.06647/) (2026)

## Abstract (arXiv)

The scope of the Sixth-Generation Self-Organized Networks (6G-SON) advances its predecessor's capability towards agility, flexibility, and adaptability. On-demand overlay networking technologies have shown a prominent maturity while coping with the rising complexity and scale of enterprise, service provider, and data centre networks. The Software-Defined Networking paradigm has recently offered Model Driven Programmability, minimizing network management complexity through automation and orchestration. However, leveraging Machine Learning-driven network optimization, a.k.a. Knowledge-Defined Networking (KDN), has still been a domain of interest for the Network Softwarization research community. In this article, we propose Intelligent Routing as a Service (iRaaS) architecture as an application layer cognitive routing framework for KDNs. iRaaS offers routing logic customization (i.e., customizing metric function and path-finding algorithm) and provides an option to include heuristic parameters from trained models as a part of the metric calculation. iRaaS sits on the application plane above the knowledge plane in a KDN stack, thus providing platform- and vendor-agnostic coupling with existing network infrastructures. This article covers the scope of iRaaS by using reliability as a heuristic for standard path-discovery algorithms, e.g., Shortest Path First (SPF) and Diffusion Update algorithm (DUAL), along with the architectural specification. We validate our approach through a Proof-of-Concept deployment.