TY - JOUR
T1 - Efficient Shortest Path Counting on Large Road Networks
AU - Qiu, Yu Xuan
AU - Wen, Dong
AU - Qin, Lu
AU - Li, Wentao
AU - Li, Rong Hua
AU - Zhang Ying.Zhang@Uts.Edu.Au, Ying
N1 - Publisher Copyright:
© 2022, VLDB Endowment., All rights reserved.
PY - 2022
Y1 - 2022
N2 - The shortest path distance and related concepts lay the foundations of many real-world applications in road network analysis. The shortest path count has drawn much research attention in academia, not only as a closeness metric accompanying the shorted distance but also serving as a building block of centrality computation. This paper aims to improve the efficiency of counting the shortest paths between two query vertices on a large road network. We propose a novel index solution by organizing all vertices in a tree structure and propose several optimizations to speed up the index construction. We conduct extensive experiments on 14 realworld networks. Compared with the state-of-the-art solution, we achieve much higher efficiency on both query processing and index construction with a more compact index.
AB - The shortest path distance and related concepts lay the foundations of many real-world applications in road network analysis. The shortest path count has drawn much research attention in academia, not only as a closeness metric accompanying the shorted distance but also serving as a building block of centrality computation. This paper aims to improve the efficiency of counting the shortest paths between two query vertices on a large road network. We propose a novel index solution by organizing all vertices in a tree structure and propose several optimizations to speed up the index construction. We conduct extensive experiments on 14 realworld networks. Compared with the state-of-the-art solution, we achieve much higher efficiency on both query processing and index construction with a more compact index.
UR - http://www.scopus.com/inward/record.url?scp=85137993342&partnerID=8YFLogxK
U2 - 10.14778/3547305.3547315
DO - 10.14778/3547305.3547315
M3 - Conference article
AN - SCOPUS:85137993342
SN - 2150-8097
VL - 15
SP - 2098
EP - 2110
JO - Proceedings of the VLDB Endowment
JF - Proceedings of the VLDB Endowment
IS - 10
T2 - 48th International Conference on Very Large Data Bases, VLDB 2022
Y2 - 5 September 2022 through 9 September 2022
ER -