Intelligent Routing as a Service (iRaaS)

TL;DR

This paper introduces iRaaS, a novel application layer framework for cognitive routing in Knowledge-Defined Networks, enabling customizable, heuristic-enhanced routing decisions to improve network agility and adaptability.

Contribution

It proposes the iRaaS architecture that allows platform- and vendor-agnostic, customizable routing with heuristic integration in KDNs, validated through a proof-of-concept deployment.

Findings

iRaaS enables routing logic customization and heuristic parameter inclusion.

The architecture integrates with existing network infrastructures seamlessly.

Validation shows effective routing optimization using reliability heuristics.

Abstract

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.