Scalable Real-Time Bandwidth Fairness in Switches
Robert MacDavid, Xiaoqi Chen, Jennifer Rexford
Abstract
Network operators want to enforce fair bandwidth sharing between users without solely relying on congestion control running on end-user devices. However, in edge networks (e.g., 5G), the number of user devices sharing a bottleneck link far exceeds the number of queues supported by today’s switch hardware; even accurately tracking per-user sending rates may become too resource-intensive. Meanwhile, traditional software-based queuing on CPUs struggles to meet the high throughput and low latency demanded by 5G users.We propose Approximate Hierarchical Allocation of Bandwidth (AHAB), a per-user bandwidth limit enforcer that runs fully in the data plane of commodity switches. AHAB tracks each user’s approximate traffic rate and compares it against a bandwidth limit, which is iteratively updated via a real-time feedback loop to achieve max-min fairness across users. Using a novel sketch data structure, AHAB avoids storing per-user state, and therefore scales to thousands of slices and millions of users. Furthermore, AHAB supports network slicing, where each slice has a guaranteed share of the bandwidth that can be scavenged by other slices when under-utilized. Evaluation shows AHAB can achieve fair bandwidth allocation within 3.1ms, 13x faster than prior data-plane hierarchical schedulers.
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