Abstract
The shortest path query is one of the hot issues in graph research. In view of the low query efficiency and poor scalability caused by the long time of the construction of index and the large scale of index in the existing methods, we propose an associated index strategy based on the single branch path vertices, which is to construct the associated index for the vertex of single branch path vertices and construct the 2-hop label index for the other vertices in order to reduce the size and construction time of index by reducing the number of redundant data storage and graph traversal. Then we propose the corresponding shortest path query algorithm based on the single branch path vertices associated index. And then, we introduce the concept of core vertex for the construction of the 2-hop label index, which can further reduce the number of graph traversal and improve the efficiency of index construction. And we apply it to the shortest path query algorithm for the large graphs. Finally, according to test on the 12 real datasets, we verify the high efficiency of the method proposed in this paper compared with the existing methods from the following aspects, such as the index construction time, the index size and the shortest path query time.
Similar content being viewed by others
References
Bader, J.S., Chaudhuri, A., Rothberg, J.M.: Gaining confidence in high-through put protein interaction networks. Nat. Biotechnol. 22(1), 78–85 (2003)
Yang, J., Li, J., Dong, L.: Stefan grünewald. a heuristic algorithm to align protein interaction networks. J. Biomath. 26(3), 569–575 (2011). (in Chinese)
Tian, Y., Mceachin, R.C., Santos, C., States, D.J., Patel, J.M.: SAGA: a subgraph matching tool for biological graphs. Bioinformatics 23(2), 32–239 (2007)
Guo, L., Shao, J., Aung, H.H., Tan, K.: Efficient continuous top-k spatial keyword queries on road networks. Geoinformatica 19(1), 29–60 (2015)
Wang, S., Xiao, X., Yang, Y., Lin, W.: Effective indexing for approximate constrained shortest path queries on large road networks. Proc. VLDB Endow. 10(2), 61–72 (2016)
Shen, B., Zhao, Y., Li, G., Rao, Y.: V-Tree: Efficient knn search on moving objects with road-network constraints. In: Proceedings of 2017 IEEE 33rd International Conference on Data Engineering(ICDE), San Diego, pp. 609–620 (2017)
Ogaard, K., Roy, H., Kase, S., Sambhoos. K.: Discovering Patterns in Social Networks with Graph Matching Algorithms. In: Proceedings of International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction, Washington, pp. 341–349 (2013)
Hao, F., Li, S., Min, G., Kim, H.C., Yau, S.S.: An efficient approach to generating location-sensitive recommendations in ad hoc social network environments. IEEE Trans. Serv. Comput. 8(3), 520–533 (2015)
Li, J., Wang, X., Deng, K. Yang, X. Sellis, T., Xu, J.: Most influential community search over large social networks. In: Proceedings of 2017 IEEE 33rd International Conference on Data Engineering(ICDE), San Diego, pp. 871–882 (2017)
Ristoski, P., Paulheim, H.: Semantic Web in data mining and knowledge discovery: a comprehensive survey. J. Web Semant. 36, 1–22 (2016)
Yu, X., Papakonstantinou., Y.: Efficient keyword search for smallest LCAs in XML databases. In: Proceedings of the 2005 ACM SIGMOD international conference on Management of data, Baltimore, pp. 527–538 (2005)
Madkour, A., Aref, W.G., Rehman, F.U., Rahman, M.A., Basalamah, S.: A survey of shortest-path algorithms. CoRR abs/1705.02044 (2017)
Deng, C., Peng, C., Wang, B., et al.: Efficient algorithm for reverse furthest neighbor in spatial databases. J. YanShan University 5, 412–419 (2013). (in Chinese)
Fu, A., Wu, H., Cheng, J., Wong, C.W.: Is-label an independent-set based labeling scheme for point-to-point distance querying. Proc. VLDB Endow. 5(1), 83–89 (2013)
Akiba, T., Iwata, Y., Yoshida, Y.: Fast exact shortest-path distance queries on large networks by pruned landmark labeling. In: Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data, NY, pp. 131–289 (2013)
Yu, X., Pu, Q.K., Koudas, N.: Monitoring k-nearest neighbor queries over moving objects. In: Proceedings of 2005 IEEE 21st International Conference on Data Engineering(ICDE), Seoul, pp. 631-642 (2005)
Gu, Y., Liu, G., Qi, J., Xu, H., Yu, G.: The Moving K Diversified Nearest Neighbor Query. In: Proceedings of 2017 IEEE 33rd International Conference on Data Engineering(ICDE), San Diego, pp. 31–32 (2017)
Zhou, J., Chen, W., Fei, C., Chen, Z.: BiRch: a bidirectional search algorithm for k-step reachability queries. J. Commun. 36(8), 50–60 (2015). (in Chinese)
Chen, Z., Chen, W., Li, N., Zhou, J.: Efficient processing algorithm for reachability queries based on big graph. Chin. J. Comput. 40(128), 1–15 (2017). (in Chinese)
Zhou, J., Zhou, S., Yu, J.X., Wei, H., Chen, Tang., Z.X.: DAGreduction: Fast answering reachability queries. In: Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data(SIGMOD), Chicago, pp. 375–390 (2017)
Chen, L., Xu, J., Lin, X., Jensen, C.S., Hu, H.: Answering why-not spatial keyword top-k queries via keyword adaption. In: Proceedings of 2016 IEEE 32nd International Conference on Data Engineering (ICDE), Helsinki, pp. 697–708 (2016)
Qiao, M., Qin, L., Cheng, H., Yu, J.X., Tian, W.: Top-k nearest keyword search on large graphs. Proc. VLDB Endow. 6(10), 901–912 (2013)
Dijkstra, E.W.: A note on two problems in connexion with graphs. Numer. Math. 1(1), 269–271 (1959)
Hart, P.E., Nilsson, N.J., Raphael, B.: A formal basis for the heuristic determination of minimum cost paths in graphs. IEEE Trans. Syst. Sci. Cybernet. 4(2), 100–107 (1968)
Bellman, R.: On a routing problem. Q. Appl. Math. 16(1), 87–90 (1958)
Johnson, D.B.: Efficient algorithms for shortest paths in sparse networks. J. ACM 24(1), 1–13 (1977)
Acknowledgements
This work is supported by the National Natural Science Foundation of China under Grant No. 61472339 and No. 61572421. The authors also gratefully acknowledge the helpful comments and suggestions of the reviewers who have improved the presentation.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Chen, W., Chen, Z., Liu, J. et al. A novel shortest path query algorithm. Cluster Comput 22 (Suppl 3), 6729–6740 (2019). https://doi.org/10.1007/s10586-018-2554-8
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10586-018-2554-8