An efficient digital search algorithm by using a double-array structure

Aoe, Jun-ichi

doi:10.1109/32.31365

Cited by 128 publications

(41 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The new suffix aa# and value 1 are appended to the end of TAIL by transferring the edge label a and TAIL[0..2]. This process is completed when BASE [6] maintains the link to TAIL [17] and element 8 becomes empty. As a result, empty elements 8 and 10, and empty spaces TAIL[0.…”

Section: Dictionary Implementationmentioning

confidence: 99%

“…A DA structure 6 represents a trie using BASE and CHECK arrays, where BASE[s] and CHECK[s] correspond to node s. The BASE and CHECK element corresponding to node s is denoted as elements. Assuming the existence of an edge from internal node s to node t with label c, the DA satisfies the following equations:…”

Section: Data Structurementioning

confidence: 99%

“…A minimal-prefix trie (MP-trie) 6,7,27 is often used to implement dictionaries. The MP-trie maintains only minimal prefixes to identify each key as nodes and the remaining suffixes as strings separately.…”

Section: Dictionary Implementationmentioning

confidence: 99%

“…Currently, a double array (DA) 6,7 is widely used to implement tries. The DA structure supports extremely fast retrieval in practical spaces.…”

Section: Introductionmentioning

confidence: 99%

“…The first objective is to improve update time. [15][16][17][18] Although the original DA trie 6 has been slow and unstable, a recent DA trie 19 enables update times that are close to those of a hashing dictionary, such as the C++ standard library's std::unordered_map. Therefore, there have been some applications using dynamic DA tries such as a full-text search engine 20 and text-stream processing.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Practical rearrangement methods for dynamic double‐array dictionaries

et al. 2017

View full text Add to dashboard Cite

SummaryDouble-array structures have been widely used to implement dictionaries with string keys. Although the space efficiency of dynamic double-array dictionaries tends to decrease with key updates, we can still maintain high efficiency using existing methods. However, these methods have practical problems of time and functionality. This paper presents several efficient rearrangement methods to solve these problems.Through experiments using real-world datasets, we demonstrate that the proposed rearrangement methods are much more practical than existing methods.

show abstract

Section: Dictionary Implementationmentioning

confidence: 99%

Section: Data Structurementioning

confidence: 99%

Section: Dictionary Implementationmentioning

confidence: 99%

“…Currently, a double array (DA) 6,7 is widely used to implement tries. The DA structure supports extremely fast retrieval in practical spaces.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Practical rearrangement methods for dynamic double‐array dictionaries

et al. 2017

View full text Add to dashboard Cite

show abstract

Fast insertion methods of a double‐array structure

Morita

Fuketa

Yamakawa

et al. 2001

Softw: Pract. Exper.

View full text Add to dashboard Cite

A double‐array is a compact and fast data structure for a trie, but it degrades the speed of insertion for a large set of keys. In this paper, two kinds of methods for improving insertion are presented. The basic functions for retrieval, insertion and deletion are implemented in the C language. Comparing with the original double‐array for large sets of keys, the improved double‐array is about six to 320 times faster than that for insertion. Copyright © 2001 John Wiley & Sons, Ltd.

show abstract

RICS‐DFA: a space and time‐efficient signature matching algorithm with Reduced Input Character Set

Tang

Jiang

Dai

et al. 2016

Concurrency and Computation

View full text Add to dashboard Cite

Summary Regular expression matching as a core component of deep packet inspection is widely used in various kinds of modern network intrusion detection system, traffic classification system, network monitoring system, and so on. In these systems, regular expressions are typically converted to a deterministic finite automaton (DFA), which takes O(1) to scan each input character. However, DFA generally consumes a large amount of memory. This paper proposes a novel, space‐efficient and time‐efficient DFA presentation, called reduced input character set DFA (RICS‐DFA). A character escaping and replacing scheme is first introduced to decrease the size of DFA's character set and then to reduce DFA's space requirement with a series of optimization techniques. Based on transition rewriting, a RICS‐DFA constructing algorithm with time complexity of O(n) is presented in this paper. For real rule‐sets, RICS‐DFA reduces the memory consumption by 68–92%, compared with the original DFA. Finally, this paper designs a scalable RICS‐DFA matching engine on field‐programmable gate array platform in which the reduced state transition matrix is mapped to on‐chip memories. The throughput of executing deep packet inspection for real rule‐sets can achieve 7–50.5 Gbps. Copyright © 2016 John Wiley & Sons, Ltd.

show abstract

An efficient digital search algorithm by using a double-array structure

Cited by 128 publications

References 17 publications

Practical rearrangement methods for dynamic double‐array dictionaries

Practical rearrangement methods for dynamic double‐array dictionaries

Fast insertion methods of a double‐array structure

RICS‐DFA: a space and time‐efficient signature matching algorithm with Reduced Input Character Set

Contact Info

Product

Resources

About