Dynamic Algorithms with Worst-Case Performance for Packet Classification

Packet classification involves -- given a set of rules -- finding the highest priority rule matching an incoming packet. When designing packet classification algorithms, three metrics need to be considered: query time, update time and storage requirements. The algorithms proposed to-date have been heuristics that exploit structure inherent in the classification rules, and/or trade off one or more metrics for others. In this paper, we describe two new simple dynamic classification algorithms, Heap-on-Trie or HoT and Binarysearchtree-on-Trie or BoT for general classifiers. The performance of these algorithms is considered in the worst-case, i.e., without assumptions about structure in the classification rules. They are also designed to perform well (though not necessarily the "best") in each of the metrics simultaneously.