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Hub Labeling for Shortest Path Counting

Published: 31 May 2020 Publication History

Abstract

The notion of shortest path is fundamental in graph analytics. While many works have devoted to devising efficient distance oracles to compute the shortest distance between any vertices s and t, we study the problem of efficiently counting the number of shortest paths between s and t in light of its applications in tasks such as betweenness-related analysis. Specifically, we propose a hub labeling scheme based on hub pushing and discuss several graph reduction techniques to reduce the index size. Furthermore, we prove several theoretical results on the performance of the scheme for some special graph classes. Our empirical study verifies the efficiency and effectiveness of the algorithms. In particular, a query evaluation takes only hundreds of microseconds in average for graphs with up to hundreds of millions of edges. We report our findings in this paper.

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Cited By

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  • (2024)Efficient Betweenness Centrality Computation over Large Heterogeneous Information NetworksProceedings of the VLDB Endowment10.14778/3681954.368200617:11(3360-3372)Online publication date: 30-Aug-2024
  • (2024)FulBM: Fast Fully Batch Maintenance for Landmark-based 3-hop Cover LabelingACM Transactions on Knowledge Discovery from Data10.1145/365003518:6(1-26)Online publication date: 29-Apr-2024
  • (2024)Parallel Contraction Hierarchies Construction on Road NetworksIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.343724336:12(9011-9024)Online publication date: Dec-2024
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    cover image ACM Conferences
    SIGMOD '20: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data
    June 2020
    2925 pages
    ISBN:9781450367356
    DOI:10.1145/3318464
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    Published: 31 May 2020

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    Author Tags

    1. algorithms
    2. counting
    3. hub labeling
    4. shortest path

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    • Research Grants Council of Hong Kong China

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    • (2024)Efficient Betweenness Centrality Computation over Large Heterogeneous Information NetworksProceedings of the VLDB Endowment10.14778/3681954.368200617:11(3360-3372)Online publication date: 30-Aug-2024
    • (2024)FulBM: Fast Fully Batch Maintenance for Landmark-based 3-hop Cover LabelingACM Transactions on Knowledge Discovery from Data10.1145/365003518:6(1-26)Online publication date: 29-Apr-2024
    • (2024)Parallel Contraction Hierarchies Construction on Road NetworksIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.343724336:12(9011-9024)Online publication date: Dec-2024
    • (2024)GPU-based butterfly countingThe VLDB Journal10.1007/s00778-024-00861-033:5(1543-1567)Online publication date: 27-Jun-2024
    • (2023)Towards Efficient Shortest Path Counting on Billion-Scale Graphs2023 IEEE 39th International Conference on Data Engineering (ICDE)10.1109/ICDE55515.2023.00198(2579-2592)Online publication date: Apr-2023
    • (2023)Double Hierarchical Labeling Shortest Distance Querying in Time-dependent Road Networks2023 IEEE 39th International Conference on Data Engineering (ICDE)10.1109/ICDE55515.2023.00161(2077-2089)Online publication date: Apr-2023
    • (2023)PSPC: Efficient Parallel Shortest Path Counting on Large-Scale Graphs2023 IEEE 39th International Conference on Data Engineering (ICDE)10.1109/ICDE55515.2023.00074(896-908)Online publication date: Apr-2023
    • (2023)Top-k Distance Queries on Large Time-Evolving GraphsIEEE Access10.1109/ACCESS.2023.331660211(102228-102242)Online publication date: 2023
    • (2022)Shortest-path queries on complex networksProceedings of the VLDB Endowment10.14778/3551793.355182015:11(2640-2652)Online publication date: 1-Jul-2022
    • (2022)Efficient shortest path counting on large road networksProceedings of the VLDB Endowment10.14778/3547305.354731515:10(2098-2110)Online publication date: Jun-2022
    • Show More Cited By

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