MEBV: Resource Optimization for Packet Classification Based on Mapping Encoding Bit Vectors

Abstract

AbstractPacket classification plays a key role in network security systems such as firewalls and QoS. The so-called packet classification is to classify packets into different categories according to a set of predefined rules. When the traditional classification algorithm is implemented based on FPGA, memory resources are wasted in storing a large number of identical rule subfields, redundant length subfields, and useless wildcards in the rules. At the same time, due to the rough processing of range matching, the rules are extended. These problems seriously waste memory resources and pose a huge challenge to FPGAs with limited hardware resources. Therefore, a field mapping encoding bit vector (MEBV) scheme is proposed, which consists of a field-splitting-recombination architecture that can accurately divide each field into four mapping preparation fields according to the matching method, field reuse rate, and wildcard ratio, and also consists of four mapping encoding algorithms to complete the length compression of the rules, to achieve the purpose of saving resources. Experimental results show that for the 1K OpenFlow 1.0 ruleset, the algorithm can achieve a significant reduction in memory resources while maintaining high throughput and support range matching, and the scheme method can save an average of 38% in memory consumption.KeywordsPacket classificationBit-vectorMemory compressionMapping encodingFPGA