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Cluster Computing

, Volume 22, Supplement 6, pp 14651–14660 | Cite as

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

  • Zhiping WanEmail author
  • Shaojiang Liu
  • Weichuan Ni
  • Zhiming Xu
Article

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.

Keywords

Underwater acoustic sensor networks Clustering Multi-level network hierarchy Routing rules 

References

  1. 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)CrossRefGoogle Scholar
  2. 2.
    Duan, Y.: Improving on HEED protocol of wireless sensor networks with sleep scheduling algorithm. J. Inf. Comput. Sci. 12(13), 5163–5173 (2015)CrossRefGoogle Scholar
  3. 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)CrossRefGoogle Scholar
  4. 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)CrossRefGoogle Scholar
  5. 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)CrossRefGoogle Scholar
  6. 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)MathSciNetCrossRefGoogle Scholar
  7. 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)CrossRefGoogle Scholar
  8. 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)MathSciNetCrossRefGoogle Scholar
  9. 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. 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)CrossRefGoogle Scholar
  11. 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)CrossRefGoogle Scholar
  12. 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)CrossRefGoogle Scholar
  13. 13.
    Darehshoorzadeh, A., Boukerche, A.: Underwater sensor networks: a new challenge for opportunistic routing protocols. IEEE. Commun. Mag. 53(11), 98–107 (2015)CrossRefGoogle Scholar
  14. 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)CrossRefGoogle Scholar
  15. 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)CrossRefGoogle Scholar
  16. 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)CrossRefGoogle Scholar
  17. 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. 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)Google Scholar
  19. 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. 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

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Zhiping Wan
    • 1
    • 3
    Email author
  • Shaojiang Liu
    • 2
  • Weichuan Ni
    • 2
  • Zhiming Xu
    • 1
  1. 1.Department of Information ScienceXinhua College of Sun Yat-Sen UniversityGuangzhouChina
  2. 2.Department of Equipment and Laboratory ManagementXinhua College of Sun Yat-Sen UniversityGuangzhouChina
  3. 3.Sun Yat-Sen UniversityGuangzhouChina

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