Taming Imbalance and Complexity in Resilient WAN Traffic Engineering
Yufeng Xin, Sajith Sasidharan, Cong Wang, Mert Cevik · 2025
The rapid expansion of global cloud infrastructures and increasing network traffic volume and dynamicity have led to a rise in research on developing scalable and resilient Traffic Engineering (TE) solutions for Wide Area Networks (WANs). Despite recent advancements, striking the right balance between network availability, computational complexity, and resource utilization remains a significant challenge.This paper presents empirical findings that highlight the inherent traffic demand imbalance and link utilization heterogeneity that current TE solutions have overlooked. We then define two new performance metrics, namely critical link set and network criticality, that jointly represent these heterogeneities. We further introduce an efficient extension to the tunnel-based resilient TE algorithm to be adaptive to traffic profiles. An extensive simulation study on representative WAN topologies demonstrates the substantial performance enhancements achieved by our holistic solution approach.