A fast retrieval technique for large graph structures

Graphs are a typical and basic data structure for computer algorithms. A two-dimensional array and a list are well-known as for their representation. These data representations have contrasting features for retrieval time and space efficiency. Aho et al. [3] proposed a method for combining the compa...

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Veröffentlicht in:	International Journal of Computer Mathematics Jg. 60; H. 3-4; S. 215 - 228
Hauptverfasser:	Iriguchi, Hirokazu, Koyama, Masashi, Shishibori, Masami, Aoe, Jun-Ichi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Abingdon Gordon and Breach Science Publishers 01.01.1996 Informa UK Limited Taylor and Francis
Schlagworte:	Algorithmics. Computability. Computer arithmetics Algorithms Applied sciences Computer science; control theory; systems Data compressing Exact sciences and technology F.2.2[Nonnumerical Algorithms and problems] Finite automata Graph structures H.3.3[Information search and retrieval] Information retrieval. Graph Performance E.1 Data Structure[Graphs] Storing and retrieving Theoretical computing Worst-case time complexity Data compression Worst case method Information retrieval Finite automaton Graph theory Data structure Algorithm Time complexity
ISSN:	0020-7160, 1029-0265
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Abstract	Graphs are a typical and basic data structure for computer algorithms. A two-dimensional array and a list are well-known as for their representation. These data representations have contrasting features for retrieval time and space efficiency. Aho et al. [3] proposed a method for combining the compactness of the list with the fast retrieval of the array. Applications of Aho's scheme were, however, limited to static data structures because the updating algorithm was not given. By introducing three one-dimensional arrays based on Aho's data structure, called a triple-array structure, this paper proposes a method for updating arcs stored in the triple-array without degrading the worst-case retrieval time complexity 0(1). The triple-array maps arcs into two one-dimensional arrays CHECK and NEXT according to another one-dimensional array BASE. An updating algorithm presented here moves the initial positions of the arcs into other possible positions in the triple-array, by a first-fit strategy which searches the array CHECK starting from the head. For a large graph, the updating algorithm is improved by introducing the criterion of searching the array CHECK locally. Theoretical and experimental observations show that the updating time of the triple-array becomes practical while keeping the worstcase retrieval time complexity 0(1).
AbstractList	Graphs are a typical and basic data structure for computer algorithms. A two-dimensional array and a list are well-known as for their representation. These data representations have contrasting features for retrieval time and space efficiency. Aho et al. [3] proposed a method for combining the compactness of the list with the fast retrieval of the array. Applications of Aho's scheme were, however, limited to static data structures because the updating algorithm was not given. By introducing three one-dimensional arrays based on Aho's data structure, called a triple-array structure, this paper proposes a method for updating arcs stored in the triple-array without degrading the worst-case retrieval time complexity O(1). The triple-array maps arcs into two one-dimensional arrays CHECK and NEXT according to another one-dimensional array BASE. An updating algorithm presented here moves the initial positions of the arcs into other possible positions in the triple array, by a first-fit strategy which searches the array CHECK starting from the head. For a large graph, the updating algorithm is improved by introducing the criterion of searching the array CHECK locally. Theoretical and experimental observations show that the updating time of the triple-array becomes practical while keeping the worstcase retrieval time complexity O(1). Graphs are a typical and basic data structure for computer algorithms. A two-dimensional array and a list are well-known as for their representation. These data representations have contrasting features for retrieval time and space efficiency. Aho et al. [3] proposed a method for combining the compactness of the list with the fast retrieval of the array. Applications of Aho's scheme were, however, limited to static data structures because the updating algorithm was not given. By introducing three one-dimensional arrays based on Aho's data structure, called a triple-array structure, this paper proposes a method for updating arcs stored in the triple-array without degrading the worst-case retrieval time complexity 0(1). The triple-array maps arcs into two one-dimensional arrays CHECK and NEXT according to another one-dimensional array BASE. An updating algorithm presented here moves the initial positions of the arcs into other possible positions in the triple-array, by a first-fit strategy which searches the array CHECK starting from the head. For a large graph, the updating algorithm is improved by introducing the criterion of searching the array CHECK locally. Theoretical and experimental observations show that the updating time of the triple-array becomes practical while keeping the worstcase retrieval time complexity 0(1).
Author	Iriguchi, Hirokazu Koyama, Masashi Aoe, Jun-Ichi Shishibori, Masami
Author_xml	– sequence: 1 givenname: Hirokazu surname: Iriguchi fullname: Iriguchi, Hirokazu organization: Department of Information Science and Intelligent Systems University of Tokushima – sequence: 2 givenname: Masashi surname: Koyama fullname: Koyama, Masashi organization: Department of Information Science and Intelligent Systems University of Tokushima – sequence: 3 givenname: Masami surname: Shishibori fullname: Shishibori, Masami organization: Department of Information Science and Intelligent Systems University of Tokushima – sequence: 4 givenname: Jun-Ichi surname: Aoe fullname: Aoe, Jun-Ichi organization: Department of Information Science and Intelligent Systems University of Tokushima
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SubjectTerms	Algorithmics. Computability. Computer arithmetics Algorithms Applied sciences Computer science; control theory; systems Data compressing Exact sciences and technology F.2.2[Nonnumerical Algorithms and problems] Finite automata Graph structures H.3.3[Information search and retrieval] Information retrieval. Graph Performance E.1 Data Structure[Graphs] Storing and retrieving Theoretical computing Worst-case time complexity
Title	A fast retrieval technique for large graph structures
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