ShareDP: Finding k Disjoint Paths for Multiple Vertex Pairs

Fuente: arXiv
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Autores principales: Yuan, Zhiqiu, Li, Youhuan, Zou, Lei, Yang, Linglin
Formato: Preprint
Publicado: 2025
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author Yuan, Zhiqiu
Li, Youhuan
Zou, Lei
Yang, Linglin
author_facet Yuan, Zhiqiu
Li, Youhuan
Zou, Lei
Yang, Linglin
contents Finding k disjoint paths (kDP) is a fundamental problem in graph analysis. For vertices s and t, paths from s to t are said to be disjoint if any two of them share no common vertex except s and t. In practice, disjoint paths are widely applied in network routing and transportation. In these scenarios, multiple kDP queries are often issued simultaneously, necessitating efficient batch processing. This motivates the study of batch kDP query processing (batch-kDP). A straightforward approach to batch-kDP extends batch simple-path enumeration with disjointness checks. But this suffers from factorial computational complexity. An alternative approach leverages single-query algorithms that avoid this by replacing the graph with a converted version. However, handling each query independently misses opportunities for shared computation. To overcome these limitations, we propose ShareDP, an algorithm for batch-kDP that shares the computation and storage across kDPs. ShareDP merges converted graphs into a shared structure, then shares the traversals and operations from different queries within this structure. Extensive experiments on 12 real-world datasets confirm the superiority of ShareDP over comparative approaches.
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id arxiv_https___arxiv_org_abs_2502_16506
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle ShareDP: Finding k Disjoint Paths for Multiple Vertex Pairs
Yuan, Zhiqiu
Li, Youhuan
Zou, Lei
Yang, Linglin
Databases
Social and Information Networks
Finding k disjoint paths (kDP) is a fundamental problem in graph analysis. For vertices s and t, paths from s to t are said to be disjoint if any two of them share no common vertex except s and t. In practice, disjoint paths are widely applied in network routing and transportation. In these scenarios, multiple kDP queries are often issued simultaneously, necessitating efficient batch processing. This motivates the study of batch kDP query processing (batch-kDP). A straightforward approach to batch-kDP extends batch simple-path enumeration with disjointness checks. But this suffers from factorial computational complexity. An alternative approach leverages single-query algorithms that avoid this by replacing the graph with a converted version. However, handling each query independently misses opportunities for shared computation. To overcome these limitations, we propose ShareDP, an algorithm for batch-kDP that shares the computation and storage across kDPs. ShareDP merges converted graphs into a shared structure, then shares the traversals and operations from different queries within this structure. Extensive experiments on 12 real-world datasets confirm the superiority of ShareDP over comparative approaches.
title ShareDP: Finding k Disjoint Paths for Multiple Vertex Pairs
topic Databases
Social and Information Networks
url https://arxiv.org/abs/2502.16506