Abstract
Fault resilient routing is a typical issue for underwater wireless sensor networks (\( UWSNs \)) due to contact of underwater creatures, mobility of nodes and natural disaster. In the existing studies, most of the researchers introduced routing scheme for routing the packets towards the base station through a cluster head. However, these schemes use static or mobile nodes for deployment, but nodes move from its original position to another position and get stuck in a particular region due to ocean current, natural disaster and environmental interference. Therefore, this leads to high energy depletion, link failure, disjoint path and overloaded data. To resolve this issue, we have proposed fault resilient routing based on moth flame optimization (\( MFO \)) scheme for transferring the packets towards the base station through autonomous underwater vehicles (\( AUVs \)). In this scheme, \( AUVs \) is used instead of cluster head to avoid the reclustering, overloading problem and it also feasible for large scale networks. There may be a disjoint path issue, so we have deployed additional mobile nodes with the help of \( AUVs \) within the network. Further, a novel fitness function is integrated with the \( MFO \) scheme to overcome the link failure problem. The proposed scheme is applied to select the best forwarding node for transmitting the packets towards the nearest \( AUVs \) using multi-hop acoustic links. In \( UWSNs \), \( AUVs \) is placed to move the packets towards the \( BS \) from lower level to upper level. Performance evaluation of proposed scheme shows better result in terms of fault resilient, residual energy, network lifetime, packet delivery ratio and convergence rate than the existing scheme under the different network scenario.
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References
Han, G., Jiang, J., Bao, N., Wan, L., & Guizani, M. (2015). Routing protocols for underwater wireless sensor networks. IEEE Communications Magazine,53(11), 72–78.
Heidemann, J., Stojanovic, M., & Zorzi, M. (2012). Underwater sensor networks: Applications, advances and challenges. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences,370(1958), 158–175.
Felemban, E., Shaikh, F. K., Qureshi, U. M., Sheikh, A. A., & Qaisar, S. B. (2015). Underwater sensor network applications: A comprehensive survey. International Journal of Distributed Sensor Networks,11(11), 896832.
Amoli, P. V. (2016). An overview on current researches on underwater sensor networks: Applications, challenges and future trends. International Journal of Electrical and Computer Engineering,6(3), 955.
Li, N., Martínez, J. F., Meneses Chaus, J., & Eckert, M. (2016). A survey on underwater acoustic sensor network routing protocols. Sensors,16(3), 414.
Darehshoorzadeh, A., & Boukerche, A. (2015). Underwater sensor networks: A new challenge for opportunistic routing protocols. IEEE Communications Magazine,53(11), 98–107.
Ghoreyshi, S. M., Shahrabi, A., & Boutaleb, T. (2017). Void-handling techniques for routing protocols in underwater sensor networks: Survey and challenges. IEEE Communications Surveys & Tutorials,19(2), 800–827.
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.
Zhou, Z., Yao, B., Xing, R., Shu, L., & Bu, S. (2015). E-CARP: An energy efficient routing protocol for UWSNs in the internet of underwater things. IEEE Sensors Journal,16(11), 4072–4082.
Ilyas, N., Alghamdi, T. A., Farooq, M. N., Mehboob, B., Sadiq, A. H., Qasim, U., et al. (2015). AEDG: AUV-aided efficient data gathering routing protocol for underwater wireless sensor networks. Procedia Computer Science,52, 568–575.
Khan, J., & Cho, H. S. (2015). A distributed data-gathering protocol using AUV in underwater sensor networks. Sensors,15(8), 19331–19350.
Kanthimathi, N. (2017). Void handling using geo-opportunistic routing in underwater wireless sensor networks. Computers & Electrical Engineering,64, 365–379.
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.
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.
Coutinho, R. W., Boukerche, A., Vieira, L. F., & Loureiro, A. A. (2015). Geographic and opportunistic routing for underwater sensor networks. IEEE Transactions on Computers,65(2), 548–561.
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.
Rahman, M. A., Lee, Y., & Koo, I. (2017). EECOR: An energy-efficient cooperative opportunistic routing protocol for underwater acoustic sensor networks. IEEE Access,5, 14119–14132.
Goyal, N., Dave, M., & Verma, A. K. (2018). A novel fault detection and recovery technique for cluster-based underwater wireless sensor networks. International Journal of Communication Systems,31(4), e3485.
Qiuli, C., Wei, X., Fei, D., & Ming, H. (2018). A reliable routing protocol against hotspots and burst for UASN-based fog systems. Journal of Ambient Intelligence and Humanized Computing, 10, 1–13.
Khasawneh, A., Latiff, M. S. B. A., Kaiwartya, O., & Chizari, H. (2018). A reliable energy-efficient pressure-based routing protocol for underwater wireless sensor network. Wireless Networks,24(6), 2061–2075.
Ahmed, F., Wadud, Z., Javaid, N., Alrajeh, N., Alabed, M., & Qasim, U. (2018). Mobile sinks assisted geographic and opportunistic routing based interference avoidance for underwater wireless sensor network. Sensors,18(4), 1062.
Albukhary, R. A., & Bouabdallah, F. (2019). Time-variant balanced routing strategy for underwater wireless sensor networks. Wireless Networks,25, 1–15.
Faheem, M., Ngadi, M. A., & Gungor, V. C. (2019). Energy efficient multi-objective evolutionary routing scheme for reliable data gathering in internet of underwater acoustic sensor networks. Ad Hoc Networks, 101912.
Wan, S., Zhang, Y., & Chen, J. (2016). On the construction of data aggregation tree with maximizing lifetime in large-scale wireless sensor networks. IEEE Sensors Journal,16(20), 7433–7440.
Chen, C., Liu, L., Qiu, T., Yang, K., Gong, F., & Song, H. (2018). ASGR: An artificial spider-web-based geographic routing in heterogeneous vehicular networks. IEEE Transactions on Intelligent Transportation Systems,20(5), 1604–1620.
Luo, H., Guo, Z., Wu, K., Hong, F., & Feng, Y. (2009). Energy balanced strategies for maximizing the lifetime of sparsely deployed underwater acoustic sensor networks. Sensors,9(9), 6626–6651.
Domingo, M. C. (2008). Overview of channel models for underwater wireless communication networks. Physical Communication,1(3), 163–182.
Mirjalili, S. (2015). Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm. Knowledge-Based Systems,89, 228–249.
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Kumari, S., Mishra, P.K. & Anand, V. Fault resilient routing based on moth flame optimization scheme for underwater wireless sensor networks. Wireless Netw 26, 1417–1431 (2020). https://doi.org/10.1007/s11276-019-02209-x
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DOI: https://doi.org/10.1007/s11276-019-02209-x