Strategies for mitigating TCAM space bottlenecks

Transport networks satisfy requests to forward data in a given topology. At the level of a network element, forwarding decisions are defined by flows. To implement desired data properties during forwarding, a network operator imposes economic models by applying policies to flows. In real applications, the number of different policies is much smaller than the number of flows. In this work, we draw from our experience in classifier design for commercial systems and demonstrate how to share classifiers that represent policies between flows while still implementing them per flow per policy state. The resulting space saving is several orders of magnitude higher than any state-of-the art methods which reduce space of classifiers representation.