Fast incremental updates on Ternary-CAMs for routing lookups and packet classification

One popular hardware device for performing fast routing lookups and packet classification is a ternary content-addressable memory (TCAM). A TCAM searches the header of the incoming packet against all entries in the forwarding table or the classifier database in parallel. It keeps the entries in decreasing order of priority of the rules in a classifier, or prefix lengths of the entries in a forwarding table. Keeping the list sorted under addition and deletion of rules in the classifier is an expensive operation, and may take O(N) memory shift (write) operations in the worst case, where N is the number of rules in the classifier (or pre- fixes in the forwarding table). The most common solutions for this problem improve average case, but waste precious TCAM space, and may still run into the worst case. This paper proposes two algorithms to manage the TCAM such that incremental update times remain small in the worst case. Analysis of these algorithms proves the optimality of one, and suggests that of the other, under the respectively imposed constraints. Finally, simulation results on real data from the Internet shows the performance benefits achievable using these algorithms.