Taming Imbalance and Complexity in WAN Traffic Engineering

TL;DR

This paper introduces a holistic approach to WAN traffic engineering that improves resilience and scalability by addressing traffic demand heterogeneity and link utilization imbalances through new metrics and a dynamic algorithm.

Contribution

It presents a novel resilient TE algorithm and comprehensive performance metrics, advancing the state-of-the-art in scalable WAN traffic management.

Findings

Significant performance improvements in diverse WAN topologies

Enhanced balance between solution quality and computational complexity

Better resilience and adaptability to traffic changes

Abstract

The rapid expansion of global cloud infrastructures, coupled with the growing volume and complexity of network traffic, has fueled active research into scalable and resilient Traffic Engineering (TE) solutions for Wide Area Networks (WANs). Despite recent advancements, achieving an optimal balance between solution quality and computational complexity remains a significant challenge, especially for larger WAN topologies under dynamic traffic demands and stringent resource constraints. This paper presents empirical evidence of a critical shortcoming in existing TE solutions: their oversight inadequately accounting for traffic demand heterogeneities and link utilization imbalances. We identify key factors contributing to these issues, including traffic distribution, solver selection, resiliency, and resource overprovisioning. To address these gaps, we propose a holistic solution featuring new performance metrics and a novel resilient TE algorithm. The proposed metrics, critical link set and network criticality, provide a more comprehensive assessment of resilient TE solutions, while the tunnel-based TE algorithm dynamically adapts to changing traffic demands. Through extensive simulations on diverse WAN topologies, we demonstrate that this holistic solution significantly improves network performance, achieving a superior balance across key objectives. This work represents a significant advancement in the development of resilient and scalable TE solutions for WANs.