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An energy-efficient multi-level adaptive clustering routing algorithm for underwater wireless sensor networks

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Abstract

Excessive energy loss is caused by premature node death and lower energy utilization efficiency in underwater acoustic sensor networks. Network-based clustering methods can use a cluster head to fuse data within the cluster members for forwarding, instead of each node forwarding data alone, which can effectively reduce the total energy loss in the process of transmission. Therefore, an energy-efficient adaptive clustering routing algorithm for underwater acoustic sensor network is proposed (ACUN). The algorithm uses a multi-level hierarchical network structure based on the distance between cluster heads and the sink node and the residual energy of a cluster head to determine the size of the competition radius. It can avoid early death of a cluster head away from the sink node because of excessive competition radius leading to excessive energy burdens. When selecting a cluster head, considering node residual energy and the energy loss of a transmission path, the algorithm can select a node with larger residual energy as a cluster head while optimizing network energy consumption. Routing rules are adopted according to the residual energy conditions of the nodes to choose a more energy-efficient single-hop routing node or multi-hop routing in favor of energy balance. Simulation experiments show that the ACUN algorithm compared with the AFP protocol and DEBCR algorithm results in more energy savings and an extended working life of network nodes.

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References

  1. Khiati, M., Djenouri, D.: BOD-LEACH: broadcasting over duty-cycled radio using LEACH clustering for delay/power efficient dissimilation in wireless sensor networks. Int. J. Commun. Syst. 28(2), 296–308 (2015)

    Article  Google Scholar 

  2. Duan, Y.: Improving on HEED protocol of wireless sensor networks with sleep scheduling algorithm. J. Inf. Comput. Sci. 12(13), 5163–5173 (2015)

    Article  Google Scholar 

  3. Pompili, D., Akyildiz, I.F.: A multimedia cross-layer protocol for underwater acoustic sensor networks. IEEE. Trans. Wirel. Commun. 9(9), 2924–2933 (2010)

    Article  Google Scholar 

  4. Nadeem, J., Naveed, I., Ashfaq, A., et al.: An efficient data-gathering routing protocol for underwater wireless sensor networks. Sensors. 15(11), 29149–29181 (2015)

    Article  Google Scholar 

  5. Jing, L., He, C., Huang, J., et al.: Energy management and power allocation for underwater acoustic sensor network. IEEE Sens. J. 17(19), 6451–6462 (2017)

    Article  Google Scholar 

  6. Junfeng, Xu, Lib, Keqiu, Min, Geyong: Asymmetric multi-path division communications in underwater acoustic networks with fading channels. J. Comput. Syst. Sci. 79(2), 269–278 (2013)

    Article  MathSciNet  Google Scholar 

  7. Bouabdallah, F., Zidi, C., Boutaba, R.: Joint routing and energy management in underwater acoustic sensor networks. IEEE. Trans. Netw. Serv. Manage. 14(2), 456–471 (2017)

    Article  Google Scholar 

  8. Coutinho, R.W.L., Boukerche, A., Vieira, L.F.M., et al.: Geographic and opportunistic routing for underwater sensor networks. IEEE. Trans. Comput. 65(2), 548–561 (2016)

    Article  MathSciNet  Google Scholar 

  9. Faheem, M., Tuna, G., Gungor, V.C.: QERP: quality-of-service (QoS) aware evolutionary routing protocol for underwater wireless sensor networks. IEEE. Syst. J. 99, 1–8 (2017)

    Google Scholar 

  10. Lee, S., Choe, H., Park, B., et al.: LUCA: an energy-efficient unequal clustering algorithm using location information for wireless sensor networks. Wirel. Pers. Commun. 56(4), 715–731 (2011)

    Article  Google Scholar 

  11. Rani, S., Ahmed, S.H., Malhotra, J., et al.: Energy efficient chain based routing protocol for underwater wireless sensor networks. J. Netw. Comput. Appl. 92(15), 42–50 (2017)

    Article  Google Scholar 

  12. Shu, T., Krunz, M.: Coverage-time optimization for clustered wireless sensor networks: a power-balancing approach. IEEE/ACM. Trans. Netw. 18(1), 202–215 (2010)

    Article  Google Scholar 

  13. Darehshoorzadeh, A., Boukerche, A.: Underwater sensor networks: a new challenge for opportunistic routing protocols. IEEE. Commun. Mag. 53(11), 98–107 (2015)

    Article  Google Scholar 

  14. Domingo, M.C., Vuran, M.C.: Cross-layer analysis of error control in underwater wireless sensor networks. Comput. Commun. 35(17), 2162–2172 (2012)

    Article  Google Scholar 

  15. Wang, K., Gao, H., Xu, X., et al.: An energy-efficient reliable data transmission scheme for complex environmental monitoring in underwater acoustic sensor networks. IEEE. Sens. J. 16(11), 4051–4062 (2016)

    Article  Google Scholar 

  16. Yang, C.H., Ssu, K.F., Yang, C.L.: A collision-analysis-based energy-efficient routing protocol in 3D underwater acoustic sensor networks. Comput. Commun. 66(24), 25–35 (2015)

    Article  Google Scholar 

  17. Qin, Z.C., Zhou, Z., Zhao, X.C.: A ring-based clustering routing protocol for WSN using particle swarm optimization. J. Beijing. Univ. P. Telecommun. 30(37), 47–50 (2012)

    Google Scholar 

  18. Yang G, Xiao M, Cheng E, et al. A cluster-head selection scheme for underwater acoustic sensor networks. Into present in 2010 international conference on communications and mobile computing, pp. 188–191. (2010)

  19. Qing-wen, W., Gang, L., Zhi, L., et al.: An adaptive forwarding protocol for underwater wireless sensor networks. J. Northwest. Polytech. Univ. 33(1), 165–170 (2015)

    Google Scholar 

  20. Ying, Z., Hong-liang, S., Chang-gang, J.: A clustered routing algorithm based on depth and energy for three-dimensional underwater sensor network. J. ShangHai. Jiao. Tong. Univ. 49(11), 1655–1659 (2015)

    Google Scholar 

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Author notes

  1. Zhiping Wan and Shaojiang Liu contributed equally to this paper.

Authors and Affiliations

  1. Department of Information Science, Xinhua College of Sun Yat-Sen University, Guangzhou, China

    Zhiping Wan & Zhiming Xu

  2. Department of Equipment and Laboratory Management, Xinhua College of Sun Yat-Sen University, Guangzhou, China

    Shaojiang Liu & Weichuan Ni

  3. Sun Yat-Sen University, Guangzhou, China

    Zhiping Wan

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  1. Zhiping Wan
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  2. Shaojiang Liu
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  3. Weichuan Ni
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  4. Zhiming Xu
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Correspondence to Zhiping Wan.

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Wan, Z., Liu, S., Ni, W. et al. An energy-efficient multi-level adaptive clustering routing algorithm for underwater wireless sensor networks. Cluster Comput 22 (Suppl 6), 14651–14660 (2019). https://doi.org/10.1007/s10586-018-2376-8

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  • DOI: https://doi.org/10.1007/s10586-018-2376-8

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