This paper addresses the problem of packet classification within a network processor (NP) architecture without the separate associative device. By the classification, we mean the process of identifying a packet by its header. The classification stage requires the implementation of data structures to store the flow tables. In our work, we consider the NP without the associative memory. Flow tables are represented by an assembly language program in the NP. For translating flow tables into assembly language programs, a tables translator was used. The main reason for implementing data compression algorithms in a flow tables translator is that modern flow tables can take up to tens of megabytes. In this paper, we describe the following data compression algorithms: Optimal rule caching, recursive end-point cutting and common data compression algorithms. An evaluation of the implemented data compression algorithms was performed on a simulation model of the NP.
A PDP-11 assembly language program for digitizing, sorting, and averaging evoked brain potentials
