Paper Info
Title
Multi-gigabit traffic identification on GPU
Abstract
Traffic Identification is a crucial task performed by ISP administrators to evaluate and improve network service quality. Deep Packet Inspection (DPI) is a well-known technique used to identify networked traffic. DPI relies mostly on Regular Expressions (REs) evaluated by Finite Automata. Many previous studies have investigated the impacts on the classification accuracy of such systems when inspecting only a portion of the traffic. However, none have discussed the real impacts on the overall system throughput. This work presents a novel technique to perform DPI on Graphics Processing Units (GPU) called Flow-Based Traffic Identification (FBTI) and a proof-of-concept prototype analysis. Basically we want to increase DPI systems? performance on commodity platforms as well as their capacity to identify networked traffic on high speed links. By combining Deterministic Finite Automaton (DFA) for evaluating REs and flow-level packet sampling we achieve a raw performance of over 60 Gbps on GPUs. Our prototype solution could reach a real throughput of over 12 Gbps, measured as the identified volume of flows.
Year
DOI
Venue
2013
10.1145/2465839.2465845
HPPN@HPDC
Keywords
Field
DocType
networked traffic,traffic identification,finite automata,dpi system,overall system throughput,novel technique,multi-gigabit traffic identification,deterministic finite automaton,flow-based traffic identification,proof-of-concept prototype analysis,prototype solution
Network service,Gigabit,Deep packet inspection,Regular expression,Deterministic finite automaton,Real-time computing,Finite-state machine,Engineering,Throughput,NetFPGA
Conference
Citations 
PageRank 
References 
3
0.42
13
Authors
5
Name
Order
Citations
PageRank
Alysson Feitoza Santos130.42
Stenio Flavio de Lacerda Fernandes270.96
Petrônio Gomes Lopes Júnior330.42
Djamel Sadok437157.81
Geza Szabo5264.74