Efficient semi-external depth-first search

•A novel and efficient semi-external DFS algorithm EP-DFS is presented.•EP-DFS requires simpler CPU calculation and less memory space.•A novel index is devised to reduce the disk random accesses.•Extensive experiments are conducted on both real and synthetic datasets. As graphs grow in size, many re...

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Vydáno v:Information sciences Ročník 599; s. 170 - 191
Hlavní autoři: Wan, Xiaolong, Wang, Hongzhi
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Inc 01.06.2022
Témata:
Depth-first search
Graph algorithm
Semi-external memory
Graph algorithm
Depth-first search
Semi-external memory
ISSN:0020-0255, 1872-6291
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Shrnutí:•A novel and efficient semi-external DFS algorithm EP-DFS is presented.•EP-DFS requires simpler CPU calculation and less memory space.•A novel index is devised to reduce the disk random accesses.•Extensive experiments are conducted on both real and synthetic datasets. As graphs grow in size, many real-world graphs are difficult to load into the primary memory of a computer. Thus, computing depth-first search (DFS) results (i.e., depth-first order or DFS-Tree) on the semi-external memory model is important to investigate. Semi-external algorithms assume that the primary memory can at least hold a spanning tree T of a graph G and gradually restructure T into a DFS-Tree, which is nontrivial. In this paper, we present a comprehensive study for the semi-external DFS problem. Based on a theoretical analysis of this problem, we introduce a new semi-external DFS algorithm called EP-DFS with a lightweight index N+-index. Unlike traditional algorithms, we focus on addressing such a complex problem efficiently with fewer I/Os, simpler CPU calculations (implementation-friendly), and less random I/O accesses (key-to-efficiency). Extensive experimental evaluations are performed on both synthetic and real graphs, and experimental results confirm that the proposed EP-DFS algorithm markedly outperforms existing algorithms.
ISSN:0020-0255
1872-6291
DOI:10.1016/j.ins.2022.03.078