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Wireless Personal Communications

, Volume 108, Issue 4, pp 2541–2558 | Cite as

Reliable Routing Algorithm Based on Clustering and Mobile Sink in Wireless Sensor Networks

  • Shayesteh TabatabaeiEmail author
  • Amir Mohsen Rigi
Article
  • 28 Downloads

Abstract

Given the limited battery energy of the sensor networks, energy efficiency is regarded as one of the most crucial issues for WSNs. In WSNs with a fixed sink, since the nodes near the sink share multi-hop routes and data and integrated towards the sink, these nodes are more likely to deplete their battery energy than other nodes of the network. Nodes’ shutdown leads to topology failure and the reduction of the sensing coverage which interrupts sensors’ data reporting tasks. In this paper, mobile sink was suggested for dealing with this problem so that load balance and uniform energy consumption can be achieved throughout the network. The proposed method, referred to as distributed clustering reliable routing protocol, operates in the distributed form and is able to minimize the reported delay. Simulation results and the comparison of the proposed protocol with NODIC protocol indicated that the proposed protocol performs better and has higher failure tolerance especially in terms of sensor nodes’ failure.

Keywords

Clustering Energy consumption WSNs (wireless sensor networks) DCRRP protocol Reliability 

Notes

References

  1. 1.
    Abasıkeles-Turgut, İ., & Hafif, O. G. (2015). NODIC: A novel distributed clustering routing protocol in WSNs by using a time-sharing approach for CH election. Wireless Network, 22, 1–12.Google Scholar
  2. 2.
    Chanak, P., & Banerjee, I. (2013). Energy efficient fault-tolerant multipath routing scheme for wireless sensor networks. The Journal of China Universities of Posts and Telecommunications, 20(6), 42–48.CrossRefGoogle Scholar
  3. 3.
    Casari, P., Nati, M., Petrioli, C., & Zorzi, M. (2006). ALBA: An adaptive load-balanced algorithm for geographic forwarding in wireless sensor networks. In Military communications conference, 2006. MILCOM 2006 (pp. 1–9). IEEE.Google Scholar
  4. 4.
    Challal, Y., Ouadjaout, A., Lasla, N., Bagaa, M., & Hadjidj, A. (2011). Secure and efficient disjoint multipath construction for fault tolerant routing in wireless sensor networks. Journal of Network and Computer Applications, 34(4), 1380–1397.CrossRefGoogle Scholar
  5. 5.
    Fyffe, M., Sun, M. T., & Ma, X. (2007). Traffic-adapted load balancing in sensor networks employing geographic routing. In Wireless communications and networking conference, 2007. WCNC 2007 (pp. 4389–4394). IEEE.Google Scholar
  6. 6.
    Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In Proceedings of the 33rd annual Hawaii international conference on system sciences, 2000 (pp. 10-pp). IEEE.Google Scholar
  7. 7.
    Sitanayah, L., Brown, K. N., & Sreenan, C. J. (2014). A fault-tolerant relay placement algorithm for ensuring k vertex-disjoint shortest paths in wireless sensor networks. Ad Hoc Networks, 23, 145–162.CrossRefGoogle Scholar
  8. 8.
    Zahedi, Z. M., Akbari, R., Shokouhifar, M., Safaei, F., & Jalali, A. (2016). Swarm intelligence based fuzzy routing protocol for clustered wireless sensor networks. Expert Systems with Applications, 55, 313–328.CrossRefGoogle Scholar
  9. 9.
    Logambigai, R., Ganapathy, S., & Kannan, A. (2018). Energy–efficient grid–based routing algorithm using intelligent fuzzy rules for wireless sensor networks. Computers & Electrical Engineering, 68, 62–75.CrossRefGoogle Scholar
  10. 10.
    OPNET, L. Specialized model. http://www.opnet.com. 2014.

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Computer EngineeringHigher Educational Complex of SaravanSaravanIran
  2. 2.Department of Computer Engineering, Zahedan BranchIslamic Azad UniversityZahedanIran

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