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Shortest path algorithm based on community detection

  • Huixiong Wang
  • , Fangyou Fu
  • , Xing Pan
  • , Xi Chen
  • Beihang University

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

To overcome the performance limitation of traditional shortest path algorithms when processing large amount of calculation in large scale networks, this article proposes a novel shortest path algorithm based on community detection. In the proposed algorithm, community detection is utilized to integrate the necessary but tedious information in the network and reduce the scale of the network, which accelerates the calculation. Particularly, when processing multiple shortest path queries, the community information can be reused, which leads to considerable improvement of the efficiency. Based on the results in performance evaluation, it turns out that in middle (500 nodes) and large-scale (1500 or 5000 nodes) BA networks, our algorithm is more efficient than traditional Dijkstra's algorithm in both single query (5%- 138%) and multiple query (104%-3905%).

源语言英语
主期刊名Proceedings - 2018 2nd European Conference on Electrical Engineering and Computer Science, EECS 2018
出版商Institute of Electrical and Electronics Engineers Inc.
361-365
页数5
ISBN(电子版)9781728119298
DOI
出版状态已出版 - 12月 2018
活动2nd European Conference on Electrical Engineering and Computer Science, EECS 2018 - Bern, 瑞士
期限: 20 12月 201822 12月 2018

出版系列

姓名Proceedings - 2018 2nd European Conference on Electrical Engineering and Computer Science, EECS 2018

会议

会议2nd European Conference on Electrical Engineering and Computer Science, EECS 2018
国家/地区瑞士
Bern
时期20/12/1822/12/18

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