Skip to main content
SpringerLink
Log in

Applying the locality principle to improve the shortest path algorithm

  • Published:
Cluster Computing Aims and scope Submit manuscript

Abstract

When shortest path algorithm be used in real time road network monitoring system, the time complexity of the algorithm is becoming the bottleneck of the system. the paper proposes a solution to improve the shortest path algorithm. By making use of the k-ary-reverse tree and locality principle, this improved algorithm keeps the data operation, in priority queue, be localized in a small range. So the time complexity of this improved shortest path algorithm is optimized from O(nlog2n) to \(O(k\times n)\); the parameter k denotes the average count of adjacency edges to each vertex, and n denotes the total count of vertexes in the network. Note that, the parameter k mainly depends on the edges density in the network. Generally speaking, the mean value of parameter k is not more than 4 in the road network, i.e. the time complexity of the improved algorithm is optimized from O(nlog2n) to O(n) in the road network. So the paper makes a conclusion that there is a linear correlation between the time complexity and the vertexes count n in the improved algorithm.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Jane, C.-C., Laih, Y.-W.: System travel time reliability: a measure of the quality of service of networks. Qual. Reliab. Eng. Int. 32(3), 805–815 (2016)

    Article  Google Scholar 

  2. Sabri, N.A.M., Basari, A.S.H.: The utilisation of Dijkstra’s algorithm to assist evacuation route in higher and close building. J. Comput. Sci. 11(2), 330–336 (2015)

    Article  Google Scholar 

  3. Hooshmand, R.-A., Fesharaki, F.H.: IEEE Trans. Smart Grid 7(1), 84–93 (2016)

  4. Zhicheng, W., Yufei, C., Zewei, Z., Weidong, Z.: An automatic panoramic image mosaic method based on graph model. Multimedia Tools Appl. 75(5), 2725–2740 (2016)

    Article  Google Scholar 

  5. Fugang, C., Han, R., Ni, C.: Finding shorter cycles in a weighted graph. Graphs Comb. 32(1), 65–77 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  6. Bin, L., Liangshan, X.: The energy conservation optimization design of the cutting edges of the twist drill based on Dijkstra’s algorithm. Int. J. Adv. Manuf. Technol. 82(5), 889–900 (2016)

  7. Wen-hong, W.E.I., Qing-xia, L.I., Zhao-quan, C.A.I.: A single-source shortest path algorithm based on the bucket structure. Comput. Eng. Sci. 34(4), 77–81 (2012)

    Google Scholar 

  8. Aini, A., Salehipour, A.: Speeding up the Floyd-Warshall algorithm for the cycled shortest path problem. Appl. Math. Lett. 25(1), 1–5 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  9. Zhenyu, M., Jeng-Shyang, P., Abdulhameed, A.: A new meta-heuristic ebb-tide-fish-inspired algorithm for traffic navigation. Telecommun. Syst. 62(2), 403–415 (2016)

    Article  Google Scholar 

  10. Galan-Garcia, J.L., Aguilera-Venegas, G., Galan-Garcia, M.A., Rodriguez-Cielos, P.: A new Probabilistic Extension of Dijkstra’s Algorithm to simulate more realistic traffic flow in a smart city. Appl. Math. Comput. 267, 780–789 (2015)

    MathSciNet  Google Scholar 

  11. Amirteimoori, A.: An extended shortest path problem: a data envelopment analysis approach. Appl. Math. Lett. 25(11), 1839–1843 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  12. He, R., Lin, B.: Dynamic Power-aware shared path protection algorithms in WDM mesh networks. J. Commun. 8(1), 55–65 (2013)

    Article  Google Scholar 

  13. Min, H., Ren, L., Lee, L.H.: Model and algorithm for 4PLRP with uncertain delivery time. Inf. Sci. 330, 211–255 (2016)

    Article  Google Scholar 

  14. Xuezhi, Z.H.U.: Shortest Path Problem Based on Genetic Algorithms(D). University of Science and Technology of China, HeFei (2015)

    Google Scholar 

  15. Sun, J., Liu, H.X.: Stochastic eco-routing in a signalized traffic network. Transp. Res Part C 7, 110–128 (2015)

    Article  Google Scholar 

  16. Wang, Q., Wang, Q.: Restricted epidemic routing in multi-community delay tolerant networks. IEEE Trans. Mobile Comput. 14(8), 1686–1697 (2015)

    Article  Google Scholar 

  17. Tan, X., Yuan, W., Tsang, D.H.: A stochastic shortest path framework for quantifying the value and lifetime of battery energy storage under dynamic pricing. IEEE Trans. Smart Grid 99, 1–10 (2015)

    Google Scholar 

  18. Cheng, J., Leung, J., Lisser, A.: New reformulations of distributionally robust shortest path problem. Comput. Oper. Res. 74, 196–204 (2016)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgements

The authors would like to thank the Science and technology project of Hebei Province(15210909), the Scientific&Technical Research Foundation of Hebei Province (15212113) and the Scientific research fund for young of North China Institute of Aerospace Engineering (KY201419) for financial support.

Author information

Authors and Affiliations

  1. School of Computer and Remote Sensing Information Technology, North China Institute of Aerospace Engineering, Langfang, 065000, Hebei, China

    Wang Xinghui, Li Jianyi, Li Xinrong & Wang Huijuan

Authors
  1. Wang Xinghui
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Li Jianyi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Li Xinrong
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Wang Huijuan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Wang Xinghui.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xinghui, W., Jianyi, L., Xinrong, L. et al. Applying the locality principle to improve the shortest path algorithm. Cluster Comput 20, 301–309 (2017). https://doi.org/10.1007/s10586-016-0696-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10586-016-0696-0

Keywords

Search

Navigation