In next-generation networks, packet classification is important in fulfilling the requirements of multimedia services, including VoIP and VoD. Using pre-defined filters, the incoming packets can be categorized that determines to which forwarding class a packet belongs. Packet classification is essentially a problem of multidimensional range matching. The tuple space search is a well-known solution based on multiple hash accesses for various filter length combinations. The tuple-based algorithm, a rectangle search, is highly scalable with respect to the number of filters; however, it suffers from the memory-explosion problem. Besides, the lookup performance of the rectangle search is not sufficiently fast to accomplish high-speed packet classification. This work proposes an improved scheme to reduce the required storage and realize OC-192 wire-speed forwarding. The scheme consists of two parts. The "Tuple Reduction Algorithm" drastically reduces the number of tuples by duplicating filters. Dynamic programming is used to optimize the tuple reduction and two heuristic approaches are introduced to simplify the optimization process. Furthermore, the "Look-ahead Caching" scheme is presented to improve the lookup performance. The basic idea is to prevent unnecessary tuple probing by filtering out the "un-matched" situation of the incoming packet. The experimental results show that combining the tuple reduction algorithm with look-ahead caching increases the lookup speed by a factor of six while requiring only around one third of the storage. Additionally, an extension of multiple fields to more general filters is addressed.

Hashing is a widely used method to perform fast lookup. Several schemes have been proposed to support Internet lookup that includes IP lookup and packet classification. Rectangular search is a well-known packet classification scheme based on multiple hash accesses for different filter length. It shows good scalability with respect to the number of filters; however, the lookup performance is not satisfactory. For example, through experiments, each packet classification takes about 40 hash accesses in a 100,000-filter database and each hash access may take more than one memory access. Obviously, this is insufficient to provide gigabits throughput. We proposed a novel "lookahead caching" which can significantly improve the performance of the hash-based algorithm. The basic idea is to find out the unmatched case for each incoming packet, thus it is different from the traditional caching mechanism. The experimental results indicate that the proposed scheme can improve the performance by a factor of two. The scheme can be further enhanced using parallel processing.

We present a novel solution to the problem of best matching prefix (BMP) which is required in the IP routing lookup. Our approach is based on the trie-based algorithm. The idea is to prune the trie so that the main-searchable portion of the trie can be fitted into the small on-chip SRAM. The algorithm consists of two parts: level smart-compression trie and trie pruning. In the first part, we present the new trie-based algorithm which can provide flexibility, storage efficiency and incremental update. Moreover, the fixed-size data structure eliminates the complexity of the memory management. Secondly, we define the "core" and present how to apply the concept "trie pruning" to achieve fast IP routing lookup. With the currently popular platform, the proposed scheme can provide 40 MPPS without any assumption. While considering route flaps, the performance degrades by only 0.01% with 4000 BGP updates per 30 seconds.