Skip to main content

Advertisement

Log in

Energy Efficient Message Priority Based Routing Protocol for Aquaculture Applications Using Underwater Sensor Network

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Aquaculture yield is determined by water characteristics of the farming area. The yield can be maximized by monitoring water parameters on a timely basis and reduces the management cost. Design of application based routing protocols are very important to gather domain specific sensory data for analysis and to achieve better performance in terms of routing techniques for packet delivery and energy consumption. Considering these issues, we propose a priority based routing (PBR) protocol for an underwater sensor architecture to monitor required water parameters used for aquaculture application. The underwater sensor nodes are deployed at various depths and moves with respect to water current forming restricted floating mobility model. The node mobility has significant influence on network performance and PBR protocol considers restricted floating mobility model. In the proposed protocol the sensor nodes reads the water parameters and the sensory data packets were prioritized by differentiating as emergency and regular. The high priority packets were transmitted using minimum delay path. To achieve efficient data packets forwarding to sink node with minimized energy consumption, routing parameters such as one hop delay, residual energy, buffer space, and node packet loss is considered to choose efficient neighbor nodes. The PBR protocol is simulated using DESERT underwater simulator to evaluate the network performance. The proposed PBR protocol outperforms in terms of packet delivery ratio, average energy consumption and network lifetime for aquaculture application using underwater sensor network, compared with existing routing protocols.

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

Access this article

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

Instant access to the full article PDF.

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
Fig. 14

Similar content being viewed by others

References

  1. Food and Agriculture Organization of the United Nations. National Aquaculture Sector Overview: India. http://www.fao.org/fishery/countrysector/naso_india/en.Accessed. 11 July 2016.

  2. Adu-Manu, K. S., Tapparello, C., Heinzelman, W., Katsriku, F. A., & Abdulai, J. D. (2017). Water quality monitoring using wireless sensor networks: Current trends and future research directions. ACM Transactions on Sensor Networks. https://doi.org/10.1145/3005719.

    Article  Google Scholar 

  3. Glasgow, H. B., Burkholder, J. M., Reed, R. E., Lewitus, A. J., & Kleinman, J. E. (2004). Real-time remote monitoring of water quality: a review of current applications and advancements in sensor, telemetry, and computing technologies. Journal of Experimental Marine Biology and Ecology, 300, 409–448.

    Article  Google Scholar 

  4. Akyildiz, I. F., Pompili, D., & Melodia, T. (2005). Underwater acoustic sensor networks: Research challenges. Ad Hoc Networks, 3(3), 257–279.

    Article  Google Scholar 

  5. Akyildiz, I. F., Pompili, D., & Melodia, T. (2007). State-of-the-art in protocol research for under-water acoustic sensor networks. ACM SIGMOBILE Mobile Computing and Communications Review, 11, 11–22.

    Article  Google Scholar 

  6. Srivastava, N. (2010). Challenges of next-generation wireless sensor networks and its impact on society. Journal of Telecommunications, 1, 128–133.

    Google Scholar 

  7. Sangwan, A., & Singh, R. P. (2015). Survey on coverage problems in wireless sensor networks. Wireless Personal Communications, 80, 1475–1500.

    Article  Google Scholar 

  8. Xu, G., Shen, W., & Wang, X. (2014). Applications of wireless sensor networks in marine environment monitoring: A survey. Sensors, 14, 16932–16954.

    Article  Google Scholar 

  9. Heidemann, J., Stojanovic, M., & Zorzi, M. (2011). Underwater sensor networks: applications, advances and challenges. Philosophical Transactions of the Royal Society, 370, 158–175.

    Article  Google Scholar 

  10. Kheirabadi, M. T., & Mohamad, M. M. (2013). Greedy routing in underwater acoustic sensor networks: A survey. International Journal of Distributed Sensor Network, 9, 1–21.

    Article  Google Scholar 

  11. Li, M., Yang, Z., & Liu, Y. (2013). Sea depth measurement with restricted floating sensors. ACM Transactions on Embedded Computing Systems, 13, 1.

    Article  Google Scholar 

  12. Masiero, R., Azad, S., & Favaro, F. (2012). DESERT underwater: An NS-Miracle-based framework to design, simulate, emulate and realize test-beds for underwater network protocols. In Oceans - Yeosu, Yeosu (pp. 1–10).

  13. Simbeye, D. S., & Zhao, J. (2014). Design and deployment of wireless sensor networks for aquaculture monitoring and control based on virtual instruments. Computers and Electronics in Agriculture, 102, 31–42.

    Article  Google Scholar 

  14. Zhua, X., Li, D., He, D., Wang, J., Ma, D., & Li, F. (2010). A remote wireless system for water quality online monitoring in intensive fish culture. Computers and Electronics in Agriculture, 71, S3–S9.

    Article  Google Scholar 

  15. Sung, W. T., Chen, J. H. (2014). Remote fish aquaculture monitoring system based on wireless transmission technology. In 2014 international conference on information science, electronics and electrical engineering, Sapporo (pp. 540–544).

  16. Garcia, M., Sendra, S., Lloret, G., & Lloret, J. (2011). Monitoring and control sensor system for fish feeding in marine fish farms. IET Communications, 5(12), 1682–1690.

    Article  Google Scholar 

  17. Lloret, J., Garcia, M., Sendra, S., & Lloret, G. (2015). An underwater wireless group-based sensor network for marine fish farms sustainability monitoring. Telecommunication Systems, 60, 67–84.

    Article  Google Scholar 

  18. Ayaz, M., et al. (2011). A survey on routing techniques in underwater wireless sensor networks. Journal of Network and Computer Applications, 34(6), 1908–1927.

    Article  Google Scholar 

  19. Wahid, A., & Dongkyun, K. (2010). Analyzing routing protocols for underwater wireless sensor networks. International Journal of Communication Networks and Information Security (IJCNIS), 2(3), 253–261.

    Google Scholar 

  20. Xie, P., Cui, J.-H., & Lao, L. (2006). VBF: Vector-based forwarding protocol for underwater sensor networks. In Networking 2006. In Networking technologies, services, and protocols; performance of computer and communication networks; mobile and wireless communications systems (pp. 1216–1221). Berlin: Springer.

    Chapter  Google Scholar 

  21. Nicolaou, N., et al. (2007). Improving the robustness of location-based routing for underwater sensor networks. In OCEANS 2007Europe, Aberdeen (pp. 1–6).

  22. Jornet, J. M., Stojanovic, M., & Zorzi, M. (2008) Focused beam routing protocol for underwater acoustic networks. In Proceedings of the third ACM international workshop on underwater networks. 2008 (pp. 75–82). San Francisco, CA: ACM.

  23. Yan, H., Shi, Z. J., & Cui, J.-H. (2008). DBR: Depth-based routing for underwater sensor networks. In Proceedings of the 7th international IFIP-TC6 networking conference on AdHoc and sensor networks, wireless networks, next generation internet (pp. 72–86). Singapore: Springer.

    Chapter  Google Scholar 

  24. Wahid, A., Lee, S., Jeong, H. J., & Kim, D. (2011). EEDBR: Energy-efficient depth-based routing protocol for underwater wireless sensor networks. In Advanced computer science and information technology, (pp. 223–234), Berlin: Springer.

    Google Scholar 

  25. Noh, Y., Lee, U., Lee, S., Wang, P., Vieira, Luiz F. M., Cui, J.-H., et al. (2016). HydroCast: Pressure routing for underwater sensor networks. IEEE Transactions on Vehicular Technology, 65(1), 333–347.

    Article  Google Scholar 

  26. Liang, W., Yu, H., Liu, L., Li, B., & Che, C. (2007). Information-carrying based routing protocol for underwater acoustic sensor network. International Conference on Mechatronics and Automation, Harbin, 2007, 729–734.

    Google Scholar 

  27. Ayaz, M., & Abdullah, A., (2009). Hop-by-hop dynamic addressing based (H2-DAB) routing protocol for underwater wireless sensor networks. In 2009 international conference on information and multimedia technology, Jeju Island, 2009 (pp. 436–441).

  28. Chenn-Jung Huanga, Y.-W., Wang, H.-H. L., Lin, C.-F., Kai-Wen, H., & Chang, Tun-Yu. (2011). A power-efficient routing protocol for underwater wireless sensor networks. Applied Soft Computing, 11(2), 2348–2355.

    Article  Google Scholar 

  29. Gopi, S., Govindan, K., Desai, U. B., Chander, D., & Merchant, S. N. (2010). E-PULRP: Energy optimized path unaware layered routing protocol for underwater sensor networks. IEEE Transactions on Wireless Communications, 9(11), 3391–3401.

    Article  Google Scholar 

  30. Tiansi, H., & Yunsi, F. (2010). QELAR: a machine-learning-based adaptive routing protocol for energy-efficient and lifetime-extended underwater sensor networks. IEEE Transactions on Mobile Computing, 9(6), 796–809.

    Article  Google Scholar 

  31. Toso, G., Masiero, R., Casari, P., Kebkal, O., Komar, M., & Zorzi, M. (2012). Field experiments for dynamic source routing: S2C EvoLogics modems run the SUN protocol using the DESERT underwater libraries. In 2012 Oceans, Hampton Roads, VA, 2012 (pp. 1–10).

  32. Toso, G., Calabrese, I., Favaro, F., Brolo, L., Casari, P. & Zorzi, M. (2014). Testing network protocols via the DESERT underwater framework: The CommsNet’13 experience. In 2014 Oceans - St. John’s, St. John’s, NL, 2014 (pp. 1–8).

  33. Ali, T., Jung, L. T., & Faye, I. (2014). End-to-end delay and energy efficient routing protocol for underwater wireless sensor networks. Wireless Personal Communications, 79(1), 339–361.

    Article  Google Scholar 

  34. Wahid, A., Sungwon, L., & Dongkyun, K. (2011). An energy-efficient routing protocol for UWSNs using physical distance and residual energy. In OCEANS 2011 IEEE - Spain, Santander, 2011 (pp. 1–6).

  35. Basagni, S., Petrioli, C., Petroccia, R., & Spaccini, D. (2015). CARP: A Channel-aware routing protocol for underwater acoustic wireless networks. Ad Hoc Networks, 34, 92–104.

    Article  Google Scholar 

  36. Zhou, Z., Yao, B., Xing, R., Shu, L., & Bu, S. (2016). E-CARP: An energy efficient routing protocol for UWSNs in the internet of underwater things. IEEE Sensors Journal, 16(11), 4072–4082.

    Article  Google Scholar 

  37. Rajesh, K. M., Rajesh, M., & Reddy, H. R. V. (2014). Assessment of microbial population in relation with hydrographical characteristics in Netravati and Gurupur estuaries off Mangalore, south-west coast of India. Ecoscan, 8, 253–256.

    Google Scholar 

  38. Oppedal, F., Dempster, T., & Stien, L. H. (2011). Environmental drivers of Atlantic salmon behaviour in sea-cages: A review. Aquaculture, 311, 1–18.

    Article  Google Scholar 

  39. Beaujean, P. P. J., Carlson, E. A., Spruance, J., & Kriel, D. (2008). HERMES–A high-speed acoustic modem for real-time transmission of uncompressed image and status transmission in port environment and very shallow water. OCEANS 2008 (pp. 1–9), Quebec City.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Shreema Shetty.

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

Shetty, S., Pai, R.M. & Pai, M.M.M. Energy Efficient Message Priority Based Routing Protocol for Aquaculture Applications Using Underwater Sensor Network. Wireless Pers Commun 103, 1871–1894 (2018). https://doi.org/10.1007/s11277-018-5886-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-018-5886-z

Keywords

Navigation