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Edge Influence Computation in Dynamic Graphs

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Database Systems for Advanced Applications (DASFAA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10178))

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Abstract

Reachability queries are of great importance in many research and application areas, including general graph mining, social network analysis and so on. Many approaches have been proposed to compute whether there exists one path from one node to another node in a graph. Most of these approaches focus on static graphs, however in practice dynamic graphs are more common. In this paper, we focus on handling graph reachability queries in dynamic graphs. Specifically we investigate the influence of a given edge in the graph, aiming to study the overall reachability changes in the graph brought by the possible failure/deletion of the edge. To this end, we firstly develop an efficient update algorithm for handling edge deletions. We then define the edge influence concept and put forward a novel computation algorithm to accelerate the computation of edge influence. We evaluate our approach using several real world datasets. The experimental results show that our approach outperforms traditional approaches significantly.

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Notes

  1. 1.

    https://www.statista.com/statistics/264810/number-of-monthly-active-facebook-users-worldwide/, retrieved December 2016.

  2. 2.

    BFS & DFS refers to Breadth-First-Search and Depth-First-Search. Both our method and BFS & DFS were performed on top of the updated labeling index.

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Acknowledgments

Authors would like to thank Xiaorong Liang for the implementation of the algorithms and thank anonymous reviewers for their valuable comments.

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Authors and Affiliations

  1. University of Huddersfield, Huddersfield, UK

    Yongrui Qin & Simon Parkinson

  2. Macquarie University, Sydney, Australia

    Quan Z. Sheng

  3. University of Adelaide, Adelaide, Australia

    Nickolas J. G. Falkner

Authors
  1. Yongrui Qin
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  2. Quan Z. Sheng
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  3. Simon Parkinson
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  4. Nickolas J. G. Falkner
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Corresponding author

Correspondence to Yongrui Qin .

Editor information

Editors and Affiliations

  1. Arizona State University, Tempe - Phoenix, Arizona, USA

    Selçuk Candan

  2. of Science and Technology, Hong Kong University of Science and Technology, Hong Kong, China

    Lei Chen

  3. Aalborg University , Aalborg, Denmark

    Torben Bach Pedersen

  4. University of New South Wales , Sydney, New South Wales, Australia

    Lijun Chang

  5. The University of Queensland , Brisbane, Queensland, Australia

    Wen Hua

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Qin, Y., Sheng, Q.Z., Parkinson, S., Falkner, N.J.G. (2017). Edge Influence Computation in Dynamic Graphs. In: Candan, S., Chen, L., Pedersen, T., Chang, L., Hua, W. (eds) Database Systems for Advanced Applications. DASFAA 2017. Lecture Notes in Computer Science(), vol 10178. Springer, Cham. https://doi.org/10.1007/978-3-319-55699-4_41

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  • DOI: https://doi.org/10.1007/978-3-319-55699-4_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55698-7

  • Online ISBN: 978-3-319-55699-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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