Shortest Path Evaluation in Wireless Network Using Fuzzy Logic

Article

Abstract

Evaluation of the shortest path in a wireless network is to ensure the fast and guaranteed delivery of the data over the established wireless network. Most of the wireless protocols are using a shortest path evaluation technique which is based on the random weights assigned to the network nodes. This alone may not be sufficient to get the accurate shortest path for routing process. Most of the shortest path evaluation algorithms perform the blind search to find the shortest routes for routing, this eventually increase the complexity of the whole process itself. This article puts some light on facts of using real time estimated routing delay from source node to other nodes by broadcasting a “knock” message. And this delay is being used to evaluate the shortest path for routing using fuzzy logic. This process is enhanced with its improved inference engine model and furnished fuzzy crisp patterns to deploy the shortest routing path in real time wireless nodes.

Keywords

Fuzzy logic Shortest path Crisp values Inference engine Wireless network 

Notes

References

  1. 1.
    Goldberg, A. V., & Radzik, T. (1993). A heuristic improvement of the Bellman–Ford algorithm. Applied Mathematics Letters, 6(3), 3–6.MathSciNetCrossRefMATHGoogle Scholar
  2. 2.
    Magzhan, K., & Jani, H. M. (2013). A review and evaluations of shortest path algorithms. International Journal of Scientific & Technology Research, 2(6), 99–104.Google Scholar
  3. 3.
    Bhuiyan, M. D. Z. A., & Wang, G. (2014). Reliable shortest paths in wireless sensor networks: Refocusing on link failure scenarios from applications. In IEEE.  https://doi.org/10.1109/prdc.2014.
  4. 4.
    Khan, P., Konar, G., & Chakraborty, N. (2014). Modification of Floyd–Warshall’s algorithm for shortest path routing in wireless sensor networks. In Annual India, IEEE conference. ISBN 978-1-4799-5364-6/14.Google Scholar
  5. 5.
    Magzhan, K., & Jani, H. M. (2013). A review and evaluations of shortest path algorithms. International Journal of Scientific and Technology Research. ISSN 2277-8616.Google Scholar
  6. 6.
    Cota-Ruiz, J., & Rivas-Perea, P. (2016). A recursive shortest path routing algorithm with application for wireless sensor network localization. IEEE Sensors Journal, 16, 4631–4637.CrossRefGoogle Scholar
  7. 7.
    Gubichev, A., Bedathur, S., & Seufert, S., & Weikum, G. (2010). Fast and accurate estimation of shortest paths in large graphs. ACM 978-1-4503-0099-5/10/10.Google Scholar
  8. 8.
    Johnson, D. B. (1977). Efficient algorithms for shortest path in sparse networks. Journal of the Association for Computer Machinery, 24(1), 1–13.MathSciNetCrossRefMATHGoogle Scholar
  9. 9.
    Jiang, J.-R., Huang, H.-W., Liao, J.-H., & Chen, S.-Y. (2014). Extending Dijikstra’s shortest path algorithm for software defined networking. APNOMS.Google Scholar
  10. 10.
    Gla, M., Musznicki, M., Nowak, P., & Zwierzykowski, P. (2013). Efficiency evaluation of shortest path algorithms. ISBN 978-1-61208-279-0, IARIA.Google Scholar
  11. 11.
    Ying, L., Shakkottai, S., Reddy, A., & Liu, S. (2010). On combining shortest-path and back-pressure routing over multihop wireless networks. IEEE/ACM TRANSACTIONS ON NETWORKING, 1063-6692.Google Scholar
  12. 12.
    Mali, G. U., & Gautam, D. K. (2017). A model application of two phase commit protocol in wireless DTN. International Journal of Computer Applications, 162(5), 23–28.CrossRefGoogle Scholar
  13. 13.
    Thippeswamy, K., Hanumanthappa, J., & Manjaiah, D. H. (2010). A study on contrast and comparison between Bellman–Ford algorithm and Dijkstra’s Algorithms. Research gate, publication/209423960Google Scholar
  14. 14.
    Abbasi-Daresari, S., & Abouei, J. (2015). Toward cluster-based weighted compressive data aggregation in wireless sensor networks. Ad Hoc Networks, Elsevier B. V.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Electronics Engineering and TechnologyNorth Maharashtra UniversityJalgaonIndia

Personalised recommendations