Skip to main content

Advertisement

SpringerLink
Log in

Distributed random cooperation for VBF-based routing in high-speed dense underwater acoustic sensor networks

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

Most of underwater wireless sensor applications need reliable data transfer timely and efficiently. Because radio waves do not travel well through good electrical conductors like saltwater, underwater distributed systems use acoustic waves to communicate data. However, energy conservation is a major challenge in underwater acoustic-based systems/networks. Different methods are developed to enhance energy efficiency in these networks. In this paper, we improve energy efficiency of the networks by enhancing routing scheme. The enhancement is done by defining some constraints on traditional packet flooding. A strategy based on physical constraints has been introduced in our previous work for creating an indirect 1-D random mechanism to remove additional nodes from routing process and save energy. Now here, a better mechanism in terms of simplicity, scalability and efficiency is introduced to improve energy consumption. The approach is to use an intelligent 3-D random node removal mechanism considering traffic status of the network. Simulation results show that the proposed approach significantly improves energy efficiency of the underwater acoustic wireless sensor networks.

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

Similar content being viewed by others

References

  1. Ayaz M, Baig I, Abdullah A, Faye I (2011) A survey on routing techniques in underwater wireless sensor networks. J Netw Comput Appl 34:1908–1927

    Article  Google Scholar 

  2. Khosravi MR, Basri H, Rostami H (2018) Efficient ROUTING FOR DENSE UWSNs with high-speed mobile nodes using spherical divisions. J Supercomput. https://doi.org/10.1007/s11227-017-2148-x

    Article  Google Scholar 

  3. Proakis JG, Rice JA, Sozer EM, Stojanovic M (2001) Shallow water acoustic networks. IEEE Commun Mag 39:114–119

    Article  Google Scholar 

  4. Sharif-Yazd M, Khosravi M, Moghimi M (2017) A survey on underwater acoustic sensor networks: perspectives on protocol design for signaling, MAC and routing. J Comput Commun 5:12–23

    Article  Google Scholar 

  5. Niculescu D, Nath B (2003) Trajectory based forwarding and its applications. In: Proceedings of the 9th Annual International Conference on Mobile Computing and Networking (MOBICOM’03), San Diego

  6. Xie P, Cui J, Lao L (2006) VBF: vector-based forwarding protocol for underwater sensor networks. In: Proceedings of the IFIP Conference: Networking Technologies, Services and Protocols Performance of Computer and Communication Networks, Mobile and Wireless Communications Systems

  7. Xie P, Zhou Z, Nicolaou N, See A, Cui J, Shi Z (2010) Efficient vector-based forwarding for underwater sensor networks. EURASIP J Wirel Commun Netw 2010:195910

    Article  Google Scholar 

  8. Pompili D, Melodia T (2005) Three-dimensional routing in underwater acoustic sensor networks. In: Proceedings of the 2nd ACM International Workshop on Performance Evaluation of Wireless Ad Hoc, Sensor, and Ubiquitous Networks (WASUN’05), Montreal

  9. Abbasi AA, Younis M (2007) A survey on clustering algorithms for wireless sensor networks. Comput Commun 30:2826–2841

    Article  Google Scholar 

  10. Yu H, Yao N, Liu J (2014) An adaptive routing protocol in underwater sparse acoustic sensor networks. Ad-Hoc Netw 34:121–143

    Article  Google Scholar 

  11. Ibrahim DM (2014) Enhancing the vector-based forwarding routing protocol for underwater wireless sensor networks: a clustering approach. In: Proceedings of the 10th International Conference on Wireless and Mobile Communications, pp 98–104

  12. Basri H, Rostami H, Khosravi MR (2015) Improvement of energy consumption in dense underwater sensor networks. In: Proceedings of the IT2015, Shahid Beheshti University (SBU), Tehran

  13. Pouryazdanpanah M (2014) DS-VBF: dual sink vector-based routing protocol for underwater wireless sensor network. In: Proceedings of the 5th Control and System Graduate Research Colloquium, Malaysia

  14. Khosravi MR, Basri H, Rostami H (2016) Energy efficient random cooperations for VBF-based routing in dense UWSNs. In: Proceedings of the ICNRAECE’16, Amirkabir University of Technology (AUT), Tehran

  15. Chen Y, Juang T, Lin Y, Tsai I (2010) A low propagation delay multi-path routing protocol for underwater sensor networks. J Internet Technol 11:153–165

    Google Scholar 

  16. Hao K, Jin Z, Shen H, Wang Y (2015) An efficient and reliable geographic routing protocol based on partial network coding for underwater sensor networks. Sensors 15:12720–12735

    Article  Google Scholar 

  17. Dhurandher SK, Obaidat MS, Gupta M (2011) An efficient technique for geocast region holes in underwater sensor, networks and its performance evaluation. Simul Model Pract Theory 19:2102–2116

    Article  Google Scholar 

  18. Dhurandher SK, Obaidat MS, Gupta M (2013) Energized geocasting model for underwater wireless sensor networks. Simul Model Pract Theory 37:125–138

    Article  Google Scholar 

  19. Ahmed M, Salleh M, Channa M (2017) Routing protocols based on node mobility for underwater wireless sensor network (UWSN): a survey. J Netw Comput Appl 78:242–252

    Article  Google Scholar 

  20. Cai S, Gao Z, Yang D, Yao N (2013) A network coding based protocol for reliable data transfer in underwater acoustic sensor. Ad Hoc Netw 11:1603–1609

    Article  Google Scholar 

  21. Sun N, Han G, Zhang J, Wu T, Jiang J, Shu L (2016) RLER: a reliable location-based and energy-aware routing protocol for underwater acoustic sensor networks. J Internet Technol 17(2):349–357

    Google Scholar 

  22. Yan H, Shi Z, Cui J (2008) DBR: depth-based routing for underwater sensor networks. In: Proceedings of the 7th IFIP-TC6 Networking Conference on Ad-Hoc and Sensor Networks

  23. Papoulis A, Pillai SU (2002) Probability, random variables, and stochastic processes. McGraw-Hill, New York

    Google Scholar 

  24. Faheem M, Tuna G, Gungor V (2017) QERP: quality-of-service (QoS) aware evolutionary routing protocol for underwater wireless sensor networks. IEEE Syst J PP:1–8

    Google Scholar 

  25. Xie P (2009) Aqua-Sim: an NS-2 based simulator for underwater sensor networks. In: Proceedings of the OCEANS2009

  26. Nicolaou N, See A, Xie P, Cui J, Maggiorini D (2007) Improving the robustness of location-based routing for underwater sensor networks. In: Proceedings of the OCEANS2007, Aberdeen

  27. Alhihi M (2017) Practical routing protocol models to improve network performance and adequacy. J Comput Commun 5:114–124

    Article  Google Scholar 

  28. Khosravi MR, Samadi S, Akbarzadeh O (2017) Determining the optimal range of angle tracking radars. In: IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI 2017), pp 3132–3135

  29. Alhihi M, Khosravi MR (2018) Formulizing the fuzzy rule for Takagi–Sugeno model in network traffic control. Open Electr Electron Eng J 12(1):1–11

    Article  Google Scholar 

  30. Torabi A, Er MJ, Li X, Lim BS (2016) Sequential fuzzy clustering based dynamic fuzzy neural network for fault diagnosis and prognosis. Neurocomputing 18:636–656

    Google Scholar 

  31. Alhihi M, Khosravi MR, Attar H, Samour M (2017) Determining the optimum number of paths for realization of multi-path routing in MPLS-TE networks. Telkomnika 15(4):1701–1709

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, Shiraz University of Technology, Shiraz, Iran

    Mohammad Reza Khosravi & Sadegh Samadi

  2. Computer Engineering Department, School of Engineering, Persian Gulf University, Bushehr, Iran

    Mohammad Reza Khosravi, Hamid Basri & Habib Rostami

  3. Department of Computer Engineering, Shiraz University, Shiraz, Iran

    Hamid Basri

Authors
  1. Mohammad Reza Khosravi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hamid Basri
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Habib Rostami
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sadegh Samadi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mohammad Reza Khosravi.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Khosravi, M.R., Basri, H., Rostami, H. et al. Distributed random cooperation for VBF-based routing in high-speed dense underwater acoustic sensor networks. J Supercomput 74, 6184–6200 (2018). https://doi.org/10.1007/s11227-018-2532-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-018-2532-1

Keywords

Search

Navigation