H-Cache: Traffic-Aware Hybrid Rule-Caching in Software-Defined Networks

Abstract

Ternary Content Addressable Memory (TCAM) is an essential hardware component in SDN-enabled switches, which supports fast lookup speed and flexible matching patterns. However, TCAM’s limited storage capacity has long been a scalability challenge to enforce fine-grained forwarding policies in SDN. Based on the observation of traffic locality, the rule-caching mechanism employs a combination of TCAM and Random Access Memory (RAM) to maintain the forwarding rules of large and small flows, respectively. However, previous works cannot identify large flows timely and accurately, and suffer from high computational complexity when addressing rule dependencies in TCAM. Worse still, TCAM only caches the forwarding rules of large flows but ignores the latency requirements of small flows. Small flows encounter cache-miss in TCAM and then will be diverted to RAM, where they have to experience slow lookup processes. To jointly optimize the performance of both high-throughput large flows and latency-sensitive small flows, we propose a hybrid rule-caching framework, H-Cache, to scale traffic-aware forwarding policies in SDN. H-Cache identifies large flows through a collaboration of learning-based and threshold-based methods to achieve early detection and high accuracy, and proposes a time-efficient greedy heuristic to address rule dependencies. For small flows, H-Cache establishes default paths in TCAM to speed up their lookup processes, and also reduces their TCAM occupancy through label switching and region partitioning. Experiments with both real-world and synthetic datasets demonstrate that H-Cache increases TCAM utilization by an average of 11% and reduces the average completion time of small flows by almost 70%.