Reconfigurable context-free grammar based data processing hardware with error recovery

Moscola,; Cho, Vincent; Lockwood,

doi:10.1109/ipdps.2006.1639489

Cited by 4 publications

(2 citation statements)

References 7 publications

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“…Furthermore, prior work on approximate protocol parsing is too inaccurate. To reduce memory usage, Moscola et al proposed ignoring the recursive structures in a grammar [12]- [14]. This crude approximate parsing is not sufficient because recursive structures often must be partially parsed to extract the desired information; for example, the second field in a function call.…”

Section: Limitations Of Prior Artmentioning

confidence: 99%

High-Speed Application Protocol Parsing and Extraction for Deep Flow Inspection

Liu

Meiners

Norige

et al. 2014

IEEE J. Select. Areas Commun.

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In this paper, we propose FlowSifter, a framework for automated online application protocol field extraction. FlowSifter is based on a new grammar model called Counting Regular Grammars (CRG) and a corresponding automata model called Counting Automata (CA). The CRG and CA models add counters with update functions and transition guards to regular grammars and finite state automata. These additions give CRGs and CAs the ability to parse and extract fields from context sensitive application protocols. These additions also facilitate fast and stackless approximate parsing of recursive structures. These new grammar models enable FlowSifter to generate optimized Layer 7 field extractors from simple extraction specifications. We compare FlowSifter against both BinPAC and UltraPAC, which represent the state-of-the-art field extractors. Our experiments show that when compared to BinPAC parsers, FlowSifter runs more than 21 times faster and uses 49 times less memory. When compared to UltraPAC parsers, FlowSifter extractors run 12 times faster and use 24 times less memory.

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Section: Limitations Of Prior Artmentioning

confidence: 99%

High-Speed Application Protocol Parsing and Extraction for Deep Flow Inspection

Liu

Meiners

Norige

et al. 2014

IEEE J. Select. Areas Commun.

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“…Unlike other parsers which use a table to look up the next state of the parser, our regular language parser converts the rules of a regular grammar into a nondeterministic finite automaton (NFA) [Moscola et al 2006c]. Representing the grammar as an NFA has two main benefits.…”

Section: Fast Regular Language Parsermentioning

confidence: 99%

Reconfigurable content-based router using hardware-accelerated language parser

Moscola

Lockwood

Cho³

2008

ACM Trans. Des. Autom. Electron. Syst.

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This article presents a dense logic design for matching multiple regular expressions with a field programmable gate array (FPGA) at 10+ Gbps. It leverages on the design techniques that enforce the shortest critical path on most FPGA architectures while optimizing the circuit size. The architecture is capable of supporting a maximum throughput of 12.90 Gbps on a Xilinx Virtex 4 LX200 and its performance is linearly scalable with size. Additionally, this article presents techniques for parsing data streams to provide semantic information for patterns found within a data stream. We illustrate how a content-based router can be implemented with our parsing techniques using an XML parser as an example. The content-based router presented was designed, implemented, and tested in a Xilinx Virtex XCV2000E FPGA on the FPX platform. It is capable of processing 32-bits of data per clock cycle and runs at 100 MHz. This allows the system to process and route XML messages at 3.2 Gbps.

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