Expanded Character Encoding for Regular Expression Filters
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Solution Overview
Problem
General-purpose hardware limitations hinder efficient regular expression matching and querying in data stores, as software applications struggle to optimize performance for specific operations, leading to suboptimal query capabilities.
Innovation Solution
Implementing expanded character encoding and hardware-optimized regular expression filters using dedicated circuitry like FPGAs or ASICs, which support metacharacters, alternations, and Kleene closures, reducing state explosions and enhancing NFA state capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If general-purpose hardware with software applications is used for regular expression matching, then versatility in deploying different query capabilities is improved, but query performance and efficiency deteriorate due to software limitations on general-purpose hardware
Solution Approach 1:
The patent replaces software-based regular expression matching on general-purpose CPUs with hardware-based matching using dedicated circuitry (FPGAs or ASICs). This substitution of mechanical/software system with hardware system achieves both high performance through dedicated optimization and versatility through reconfigurable logic, resolving the contradiction between performance and adaptability
Solution Approach 2:
The hardware implementation uses reconfigurable logic elements that can be programmed to support multiple regular expression operations and metacharacters. This multi-functionality allows the same hardware to perform various query capabilities while maintaining optimized performance, addressing both versatility and productivity requirements
2Adaptability or versatility
If traditional character encoding is used in regular expression filters, then hardware resource utilization is simple, but the ability to support metacharacters and complex patterns deteriorates
Solution Approach 1:
The patent expands the character encoding from traditional 8-bit to 9-bit encoding, creating additional encoding space that can represent metacharacters and complex pattern symbols. This parameter change in encoding capacity enables enhanced metacharacter support while the hardware efficiently manages the increased complexity through optimized state machine design
Solution Approach 2:
By adding an additional bit dimension to the character encoding (8-bit to 9-bit), the patent creates new encoding capacity without fundamentally redesigning the hardware architecture. This dimensional expansion allows metacharacter support while maintaining relatively simple hardware resource utilization through extended encoding rather than complex structural changes
3Adaptability or versatility
If expanded character encoding with 9-bit symbols is implemented, then metacharacter support and pattern capabilities are improved, but encoding complexity and processing overhead increase
Solution Approach 1:
The patent performs preliminary encoding of input strings into the expanded 9-bit symbol format before regular expression matching begins. This pre-encoding step converts the input data into a format that the hardware can efficiently process, reducing processing complexity during the actual matching operation and enabling comprehensive pattern expression capability
Data Source
AI summary
Expanded encoding may be implemented to enhance regular expression filter capabilities. Two or more adjacent characters in a stream of characters to be processed by a regular expression filter may be recognized and replaced with a symbol. The symbol may be used instead of the two or more adjacent characters for processing through non-deterministic finite automaton (NFA) states. The output of the NFA states may indicate whether a match for a regular expression is present in the stream of characters.