Title
A Memory Optimized Architecture for Multi-Field Packet Classification (Brief Announcement).
Abstract
The high-performance hardware architectures for multi-field packet classification have been studied over the past decade. Although many FPGA-based solutions can achieve very high throughput, the limited FPGA resources severely hinders the scalability of the rule-sets or matching fields. To address this issue, we present a parallel architecture named Wildcard-removed Two-dimensional Pipeline (WeeTP) to save memory usage of wildcards and reduce logic resources. WeeTP uses the Maximum Wildcard Overlap (MWO) algorithm to maximize the compression percentage by rearranging the ruleset. We implement and evaluate WeeTP on an Intel STRATIX V FPGA. Experimental results show that our approach can save 37% and 41% memory consumption on average for real 5-tuple rules and OpenFlow rules, respectively.
Year
DOI
Venue
2019
10.1145/3323165.3323171
SPAA'19: PROCEEDINGS OF THE 31ST ACM SYMPOSIUM ON PARALLELISM IN ALGORITHMS AND ARCHITECTURESS, 2019
Keywords
Field
DocType
Packet Classification,FPGA,Two-dimensional Pipeline,Wildcard Compression
Stratix,Computer architecture,Wildcard,Architecture,Wildcard character,Computer science,Parallel computing,Field-programmable gate array,OpenFlow,Throughput,Scalability
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Chenglong Li164.18
Tao Li2387.33
Junnan Li303.38
Hui Yang4113.22
Baosheng Wang55411.05