On the Impact of Caching for High Performance Packet Classifiers

Hash functions have a space complexity of O(n) and a possible time complexity of 0(1). Thus, packet classifiers exploit hashing to achieve packet classification in wire speed. Especially evolvable hash functions can adapt to a changing classification data base. But hash functions do have an important flaw. Some of the hashed keys may result in a large number of collisions. If those keys occur frequently, overall performance of a hash based packet classifier suffers. Although there is only limited or no existing locality in the data to be computed by a packet classifier, utilizing a cache can solve this problem. Unlike classical caches known from microprocessors, which are not adequate for packet classification and lookup algorithms, the proposed cache bases on a different strategy. It caches only the keys producing the most collisions instead of the ones that occur most often. That way, a cache improves the worst case performance of a hash function-based classifier. Based on simulation results, we show that even the mean performance improves significantly.