Neural network pathways: Visualizing iRaaS decision intelligence in modern infrastructure

This article explores Intelligent Routing as a Service (iRaaS), a transformative approach to network routing that leverages machine learning to overcome the limitations of traditional protocols. The article explores how iRaaS employs dynamic adaptability, service orientation, and context awareness to address the challenges of increasingly complex network environments. The discussion first examines core architectural elements, exploring both microservice structures and machine learning pipelines. It then advances to a comparative evaluation of performance metrics, contrasting the system against traditional routing approaches and demonstrating significant enhancements in response time, processing capacity, and system stability. The article further shows security and governance frameworks necessary for iRaaS implementation, including threat models specific to AI-driven routing and compliance considerations. The article concludes by investigating future research directions, particularly integration with intent-based networking, edge computing applications, standardization efforts, and emerging use cases across government, finance, healthcare, and enterprise sectors.

Authors

Publication Details

Journal
World Journal of Advanced Engineering Technology and Sciences
Published
2025-06-19
DOI
https://doi.org/10.30574/wjaets.2025.15.3.1109
Primary Topic
Information and Cyber Security
Type
article
Field-Weighted Citation Impact
0.00
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article

Neural network pathways: Visualizing iRaaS decision intelligence in modern infrastructure

حميد سلطان علي
World Journal of Advanced Engineering Technology and Sciences
Information and Cyber Security
article

Neural network pathways: Visualizing iRaaS decision intelligence in modern infrastructure

حميد سلطان علي
article en

Abstract

This article explores Intelligent Routing as a Service (iRaaS), a transformative approach to network routing that leverages machine learning to overcome the limitations of traditional protocols. The article explores how iRaaS employs dynamic adaptability, service orientation, and context awareness to address the challenges of increasingly complex network environments. The discussion first examines core architectural elements, exploring both microservice structures and machine learning pipelines. It then advances to a comparative evaluation of performance metrics, contrasting the system against traditional routing approaches and demonstrating significant enhancements in response time, processing capacity, and system stability. The article further shows security and governance frameworks necessary for iRaaS implementation, including threat models specific to AI-driven routing and compliance considerations. The article concludes by investigating future research directions, particularly integration with intent-based networking, edge computing applications, standardization efforts, and emerging use cases across government, finance, healthcare, and enterprise sectors.

World Journal of Advanced Engineering Technology and SciencesVol. 15(3)
Industry, innovation and infrastructure
Openalex Percentile: Top 80%
Information and Cyber Security
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