Skip to main content

Advertisement

SpringerLink
Log in

An energy-efficient distributed node clustering routing protocol with mobility pattern support for underwater wireless sensor networks

  • Original Paper
  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

Underwater Wireless Sensor Networks (UWSN) has received more attention in exploring promising technologies for scientific data collection of underwater natural resources with maximum link reliability. For effective communication among the sensor nodes, reliable data delivery based routing protocols have been designed to avoid long-distance communication in large network areas. But the network-based protocols suffer from many constraints like limited distance-dependent bandwidth, defective channels and high delay. Furthermore, the supplied batteries have limited power and also data transmission cannot be exploited in the long-distance network areas due to the harsh underwater environment. Therefore, a clustering-based mobility pattern routing protocol is required to link long-distance communication over depth areas with less consumed energy and less delay. This paper proposed an energy-efficient Distributed Node Clustering Mobility Pattern Routing Protocol (DNC-MPRP) to reach the long-distance depth area for data transmission with less energy consumption and avoid inaccurate routing paths using mobility patterns in UWSN. This approach consists of several phases: network initialization, Cluster Head (CH) formation and data transmission. In DNC-MPRP, the network is partitioned into two dense areas for near and far distance communications. Then the network configuration initializes the rectangle mobility pattern which is used to reach the surface sink with less delay. Next, the CH formation initializes the cluster area in the large and common area to maintain energy in the collected member nodes. Lastly, the data transmission is adopted only when the coverage area is in the transmission range of the network field. Simulation result depicts that the DNC-MPRP approach would be evaluated in terms of Energy Consumption (EC), Packet Delivery Ratio (PDR), End to End Delay (E2ED) and Network Lifetime (NL) based on the variation of nodes, different transmission range, mobile sink, data rate and payload data with high PDR of 95%, high NL of 1200 s, low E2ED of 9.5 s and less EC than existing methods.

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
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  1. Ahmed, M., Salleh, M., & Channa, M. I. (2017). Routing protocols based on node mobility for Underwater Wireless Sensor Network (UWSN): A survey. Journal of Network and Computer Applications., 78, 242–252.

    Article  Google Scholar 

  2. Cheng, C. F., & Li, L. H. (2017). Data gathering problem with the data importance consideration in underwater wireless sensor networks. Journal of Network and Computer Applications, 78, 300–312.

    Article  Google Scholar 

  3. Rahman, Z., Hashim, F., Rasid, M. F., & Othman, M. (2018). Totally opportunistic routing algorithm (TORA) for underwater wireless sensor network. PLoS ONE, 13(6), e0197087.

    Article  Google Scholar 

  4. Gjanci, P., Petrioli, C., Basagni, S., Phillips, C. A., Bölöni, L., & Turgut, D. (2017). Path finding for maximum value of information in multi-modal underwater wireless sensor networks. IEEE Transactions on Mobile Computing, 17(2), 404–418.

    Article  Google Scholar 

  5. Aghababaiyan, K., Zefreh, R. G., & Shah-Mansouri, V. (2018). 3D-OMP and 3D-FOMP algorithms for DOA estimation. Physical Communication., 31, 87–95.

    Article  Google Scholar 

  6. Dehghani, M., & Aghababaiyan, K. (2018). FOMP algorithm for direction of arrival estimation. Physical Communication., 26, 170–174.

    Article  Google Scholar 

  7. Goyal, N., Dave, M., & Verma, A. K. (2016). Energy efficient architecture for intra and inter cluster communication for underwater wireless sensor networks. Wireless Personal Communications, 89(2), 687–707.

    Article  Google Scholar 

  8. Javaid, N., Hussain, S., Ahmad, A., Imran, M., Khan, A., & Guizani, M. (2017). Region based cooperative routing in underwater wireless sensor networks. Journal of Network and Computer Applications, 92, 31–41.

    Article  Google Scholar 

  9. Yahya, A., Islam, S. U., Zahid, M., Ahmed, G., Raza, M., Pervaiz, H., & Yang, F. (2019). Cooperative routing for energy efficient underwater wireless sensor networks. IEEE Access, 7, 141888–141899.

    Article  Google Scholar 

  10. Jiang, J., Han, G., Guo, H., Shu, L., & Rodrigues, J. J. (2016). Geographic multipath routing based on geospatial division in duty-cycled underwater wireless sensor networks. Journal of Network and Computer Applications, 59, 4–13.

    Article  Google Scholar 

  11. Khan, M.T.R., Ahmed, S.H., Kim, D., (2018). AUV-assisted energy-efficient clustering in underwater wireless sensor networks, In 2018 IEEE Global Communications Conference (GLOBECOM) IEEE, 1–7.

  12. Khan, Z. A., Awais, M., Alghamdi, T. A., Khalid, A., Fatima, A., Akbar, M., & Javaid, N. (2019). Region aware proactive routing approaches exploiting energy efficient paths for void hole avoidance in underwater WSNs. IEEE Access., 7, 140703–140722.

    Article  Google Scholar 

  13. Majid, A., Azam, I., Waheed, A., Zain-ul-Abidin, M., Hafeez, T., Khan, Z.A., Javaid, N. (2016). An energy efficient and balanced energy consumption cluster based routing protocol for underwater wireless sensor networks, In 2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA) IEEE, 324–333.

  14. Rani, S., Ahmed, S. H., Malhotra, J., & Talwar, R. (2017). Energy efficient chain based routing protocol for underwater wireless sensor networks. Journal of Network and Computer Applications, 92, 42–50.

    Article  Google Scholar 

  15. Wang, J., Shi, W., Xu, L., Zhou, L., & Niu, Q. (2017). Design of optical-acoustic hybrid underwater wireless sensor network. Journal of Network and Computer Applications, 92, 59–67.

    Article  Google Scholar 

  16. Shaikh, S.N., Shaikh, N.N., Jokhio, S.H., Jokhio, I.A. (2018). Lightweight and robust data collection in a UWSN using a mobile sink, In 2018 IEEE International Conference on Innovative Research and Development (ICIRD) IEEE, 1–6.

  17. Novák, M., Ovaliadis, K., & Křehlík, Š. (2018). A hyperstructure model of underwater wireless sensor network (UWSN) design. In AIP Conference Proceedings AIP Publishing LLC, 1978(1), 340006.

    Article  Google Scholar 

  18. Sandeep, D. N., & Kumar, V. (2017). Review on clustering, coverage and connectivity in underwater wireless sensor networks: A communication techniques perspective. IEEE Access., 5, 11176–11199.

    Article  Google Scholar 

  19. Nayyar, A., Puri, V., Le, D.N. (2019). Comprehensive analysis of routing protocols surrounding underwater sensor networks (UWSNs), In Data Management Analytics and Innovation Springer Singapore, 435–450.

  20. Jouhari, M., Ibrahimi, K., Benattou, M., (2015), Topology control through depth adjustment and transmission power control for UWSN routing protocols, In 2015 International Conference on Wireless Networks and Mobile Communications (WINCOM) IEEE, 1–5.

  21. Chao, C. M., Lu, M. W., & Lin, Y. C. (2014). Energy-efficient multichannel MAC protocol design for bursty data traffic in underwater sensor networks. IEEE Journal of oceanic engineering, 40(2), 269–276.

    Article  Google Scholar 

  22. Goyal, N., Dave, M., Verma, A.K. (2016). Congestion control and load balancing for cluster based underwater wireless sensor networks. In 2016 Fourth International Conference on Parallel, Distributed and Grid Computing (PDGC) IEEE, 462–467.

  23. Gul, S., Jokhio, S.H., Jokhio, I.A. (2018) Light-weight depth-based routing for underwater wireless sensor network. In2018 International Conference on Advancements in Computational Sciences (ICACS) IEEE, 1–7.

  24. Khan, T., Ahmad, I., Aman, W., Azam, I., Khan, Z.A., Qasim, U., Avais, S., Javaid, N. (2016). Clustering depth based routing for underwater wireless sensor networks. In 2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA) IEEE, 506–515.

  25. Ahmed, F., Gul, S., Khalil, M.A., Sher, A., Khan, Z.A., Qasim, U., Javed, N. (2017) Two hop adaptive routing protocol for underwater wireless sensor networks. In InInternational Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, Springer, Cham, 181–189.

  26. Khasawneh, A., Abd Latiff, M. S., Kaiwartya, O., & Chizari, H. (2018). A reliable energy-efficient pressure-based routing protocol for underwater wireless sensor network. Wireless Networks., 24(6), 2061–2075.

    Article  Google Scholar 

  27. Ahmed, M., Salleh, M., & Channa, M. I. (2018). CBE2R: Clustered-based energy efficient routing protocol for underwater wireless sensor network. International Journal of Electronics., 105(11), 1916–1930.

    Article  Google Scholar 

  28. Pari, S.N., Sathish, M., Arumugam, K. (2018). An energy-efficient and reliable depth-based routing protocol for underwater wireless sensor network (ER-DBR), In Advances in power systems and energy management Springer Singapore, 451–463.

  29. Hao, K., Shen, H., Liu, Y., Wang, B., & Du, X. (2018). Integrating localization and energy-awareness: A novel geographic routing protocol for underwater wireless sensor networks. Mobile Networks and Applications, 23(5), 1427–1435.

    Article  Google Scholar 

  30. Gomathi, R. M., & Manickam, J. M. L. (2018). Energy efficient shortest path routing protocol for underwater acoustic wireless sensor network. Wireless Personal Communications, 98(1), 843–856.

    Article  Google Scholar 

  31. Li, X., Wang, C., Yang, Z., Yan, L., & Han, S. (2018). Energy-efficient and secure transmission scheme based on chaotic compressive sensing in underwater wireless sensor networks. Digital Signal Processing, 81, 129–137.

    Article  Google Scholar 

  32. Banaeizadeh, F., & Haghighat, A. T. (2020). An energy-efficient data gathering scheme in underwater wireless sensor networks using a mobile sink. International Journal of Information Technology, 12(2), 513–522.

    Article  Google Scholar 

  33. Alasarpanahi, H., Ayatollahitafti, V., & Gandomi, A. (2020). Energy-efficient void avoidance geographic routing protocol for underwater sensor networks. International Journal of Communication Systems., 33(6), e4218.

    Article  Google Scholar 

  34. Nazib, R. A., & Moh, S. (2021). Energy-efficient and fast data collection in UAV-aided wireless sensor networks for hilly terrains. IEEE Access., 9, 23168–23190.

    Article  Google Scholar 

  35. Mazinani, S. M., Yousefi, H., & Mirzaie, M. (2018). A vector-based routing protocol in underwater wireless sensor networks. Wireless Personal Communications, 100(4), 1569–1583.

    Article  Google Scholar 

  36. Rahman, Z., Hashim, F., Rasid, M. F. A., Othman, M., & Alezabi, K. A. (2020). Normalized advancement based totally opportunistic routing algorithm with void detection and avoiding mechanism for underwater wireless sensor network. IEEE Access, 8, 67484–67500.

    Article  Google Scholar 

  37. Ismail, M., Islam, M., Ahmad, I., Khan, F. A., Qazi, A. B., Khan, Z. H., Wadud, Z., & Al-Rakhami, M. (2020). Reliable path selection and opportunistic routing protocol for underwater wireless sensor networks. IEEE Access., 8, 100346–100364.

    Article  Google Scholar 

  38. Adil, M., Khan, R., Ali, J., Roh, B. H., Ta, Q. T., & Almaiah, M. A. (2020). An energy proficient load balancing routing scheme for wireless sensor networks to maximize their lifespan in an operational environment. IEEE Access., 8, 163209–163224.

    Article  Google Scholar 

  39. Adil, M., Khan, R., Almaiah, M. A., Binsawad, M., Ali, J., Al Saaidah, A., & Ta, Q. T. (2020). An efficient load balancing scheme of energy gauge nodes to maximize the lifespan of constraint oriented networks. IEEE Access., 8, 148510–148527.

    Article  Google Scholar 

  40. Khan, Z. A., Latif, G., Sher, A., Usman, I., Ashraf, M., Ilahi, M., & Javaid, N. (2019). Efficient routing for corona based underwater wireless sensor networks. Computing, 101(7), 831–856.

    Article  MathSciNet  Google Scholar 

  41. Arunkumar, J. R., Anusuya, R., Rajan, M. S., & Prabhu, M. R. (2020). Underwater wireless information transfer with compressive sensing for energy efficiency. Wireless Personal Communications, 113(2), 715–725.

    Article  Google Scholar 

  42. Arafat, M. Y., Habib, M. A., & Moh, S. (2020). Routing protocols for UAV-aided wireless sensor networks. Applied Sciences, 10(12), 4077.

    Article  Google Scholar 

  43. Elshrkawey, M., Elsherif, S. M., & Wahed, M. E. (2018). An enhancement approach for reducing the energy consumption in wireless sensor networks. Journal of King Saud University-Computer and Information Sciences., 30(2), 259–267.

    Article  Google Scholar 

  44. Nasir, H., Javaid, N., Ashraf, H., Manzoor, S., Khan, Z.A., Qasim, U., Sher, M. (2014). CoDBR: Cooperative depth based routing for underwater wireless sensor networks. In 2014 Ninth International Conference on Broadband and Wireless Computing, Communication and Applications IEEE, 52–57.

  45. Azam, I., Majid, A., Ahmad, I., Shakeel, U., Maqsood, H., Khan, Z.A., Javaid, N. (2016 ). SEEC: Sparsity-aware energy efficient clustering protocol for underwater wireless sensor networks, In 2016 IEEE 30th international conference on advanced information networking and applications (AINA), IEEE, 352–361.

Download references

Funding

There is no funding for this study.

Author information

Authors and Affiliations

  1. Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, 600119, India

    T. R. Chenthil & P. Jesu Jayarin

Authors
  1. T. R. Chenthil
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. P. Jesu Jayarin
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All the authors have participated in writing the manuscript and have revised the final version. All authors read and approved the final manuscript.

Corresponding author

Correspondence to T. R. Chenthil.

Ethics declarations

Conflict of interest

Authors declares that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants and/or animals performed by any of the authors.

Informed consent

There is no informed consent for this study.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chenthil, T.R., Jesu Jayarin, P. An energy-efficient distributed node clustering routing protocol with mobility pattern support for underwater wireless sensor networks. Wireless Netw 28, 3367–3390 (2022). https://doi.org/10.1007/s11276-022-03061-2

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-022-03061-2

Keywords

Search

Navigation