ARION: Aggregated Routing for In-Order Optimized Network Load Balancing in Data Centers

Abstract

Modern data center networks support a wide range of applications with dynamic and diverse traffic patterns, necessitating effective load balancing to ensure performance and scalability. This paper presents ARION, a novel distributed load balancing algorithm designed for leaf-spine architectures. ARION utilizes flow aggregation and real-time link utilization metrics, enabling each leaf switch to make informed, congestionaware routing decisions without requiring any hardware modifications to the spine switches. This approach enables effective load distribution while substantially reducing packet reordering and associated overhead. We establish a theoretical framework to assess ARION’s performance, including convergence properties and a performance bound, demonstrating that it operates within a factor of 2 of the optimal solution under heavy loads. Comprehensive simulations covering various workloads and traffic types reveal that ARION consistently outperforms common alternatives such as ECMP, CONGA, DRILL, and LetFlow, achieving a superior balance between optimal load distribution and minimal packet reordering. ARION offers a scalable, low-overhead solution for the evolving demands of data center environments.