Abstract
In Underwater Acoustic Sensor Network (UWASN), node redeployment strategy is utilized to handle the reliable network coverage. The sensors deployed in the underwater are used to intellect the area and collected information is moved to the sink node. Node redeployment strategy is essential for the nodes which are placed outside the monitoring area in UWASN. In this paper, the node redeployment strategy is performed based on the hybrid Emperor Penguin Optimization (EPO) algorithm with Particle Search Algorithm (PSO) for better underwater acoustic communication and the proposed method is named as HEPSO. This hybridization is performed to reduce node failure rate and network energy consumption rate by optimally place the sensor nodes in underwater acoustic communication. The stability of the network topology is guaranteed by this algorithm and it enhances the node redeployment strategy by calculating the fitness function for each and every node. The implementation of the proposed algorithm is carried out by the MATLAB platform. The performance parameters like network coverage rate, network connectivity rate, network lifetime, number of nodes outside monitored space and total movement distance of nodes are evaluated and related with current methods like NRBSCT (Node Redeployment Based on Stratified Connected Tree) and MRNR (Moving Redundancy Nodes Redeployment) strategy.
Similar content being viewed by others
References
Awan, K. M., Shah, P. A., Iqbal, K., Gillani, S., Ahmad, W., & Nam, Y. (2019). Underwater wireless sensor networks: A review of recent issues and challenges. Wireless Communications and Mobile Computing, 2019, 1–20.
Khasawneh, A., Abd Latiff, M. S., Kaiwartya, O., & Chizari, H. (2018). A reliable energy-efficient pressure-based routing protocol for underwater wireless sensor network. Wireless Networks, 24(6), 2061–2075.
Geethu, K. S., & Babu, A. V. (2015). Minimizing the total energy consumption in multi-hop UWASNs. Wireless Personal Communications., 83(4), 2693–2709.
Manjula, R.B., Manvi, S.S. (2013 Oct 23). Coverage optimization based sensor deployment by using PSO for anti-submarine detection in UWASNs. In 2013 Ocean Electronics (SYMPOL) IEEE. (pp. 15–22).
Han, G., Jiang, J., Sun, N., & Shu, L. (2015). Secure communication for underwater acoustic sensor networks. IEEE Communications Magazine, 53(8), 54–60.
Zenia, N. Z., Aseeri, M., Ahmed, M. R., Chowdhury, Z. I., & Kaiser, M. S. (2016). Energy-efficiency and reliability in MAC and routing protocols for underwater wireless sensor network: A survey. Journal of Network and Computer Applications, 71, 72–85.
Karim, L., Mahmoud, Q. H., Nasser, N., Anpalagan, A., & Khan, N. (2017). Localization in terrestrial and underwater sensor-based m2m communication networks: Architecture, classification and challenges. International Journal of Communication Systems, 30(4), e2997.
Wang, J., Shi, W., Xu, L., Zhou, L., & Niu, Q. (2017). Design of optical-acoustic hybrid underwater wireless sensor network. Journal of Network and Computer Applications., 92, 59–67.
Kaushal, H., & Kaddoum, G. (2016). Underwater optical wireless communication. IEEE access, 4, 1518–1547.
Senel, F. (2016). Coverage-aware connectivity-constrained unattended sensor deployment in underwater acoustic sensor networks. Wireless Communications and Mobile Computing, 16(14), 2052–2064.
Senel, F., Akkaya, K., Erol-Kantarci, M., & Yilmaz, T. (2015). Self-deployment of mobile underwater acoustic sensor networks for maximized coverage and guaranteed connectivity. Ad Hoc Networks, 34, 170–183.
Bahcebasi, A., Gungor, V.C., Tuna, G. (2018). Performance analysis of different modulation schemes for underwater acoustic communications. In 2018 3rd International Conference on Computer Science and Engineering (UBMK) IEEE. (pp. 396–401).
Kim, S., & Choi, J. (2017). Optimal deployment of sensor nodes based on performance surface of underwater acoustic communication. Sensors, 17(10), 2389.
Ahmad, A. M., Barbeau, M., Garcia-Alfaro, J., Kassem, J., & Kranakis, E. (2019). Tuning the demodulation frequency based on a normalized trajectory model for mobile underwater acoustic communications. Transactions on Emerging Telecommunications Technologies. https://doi.org/10.1002/ett.3712
Nam, H. (2017). AUV based data-gathering protocol for the lifetime extension of underwater acoustic sensor networks. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, 100(7), 1596–1600.
Bharamagoudra, M. R., & Manvi, S. S. (2017). Agent-based secure routing for underwater acoustic sensor networks. International Journal of Communication Systems, 30(13), e3281.
Nam, H. (2018). Data-gathering protocol-based AUV path-planning for long-duration cooperation in underwater acoustic sensor networks. IEEE Sensors Journal, 18(21), 8902–8912.
Liu, Y., Fang, G., Chen, H., Xie, L., Fan, R., Su, X. (2018). Error analysis of a distributed node positioning algorithm in underwater acoustic sensor networks. In 2018 10th International Conference on Wireless Communications and Signal Processing (WCSP) IEEE. (pp. 1–6) .
Sivakumar, V., & Rekha, D. (2018). Node scheduling problem in underwater acoustic sensor network using genetic algorithm. Personal and Ubiquitous Computing, 22(5–6), 951–959.
Khan, A., Khan, M., & Ahmed, S. (2018). Delay and throughput analysis using node density as pivot value in UWASNs. Adhoc and Sensor Wireless Networks, 40(5), 605–612.
Song, X., Gong, Y., Jin, D., & Li, Q. (2019). Nodes deployment optimization algorithm based on improved evidence theory of underwater wireless sensor networks. Photonic Network Communications, 37(2), 224–232.
Jiang, P., Feng, Y., & Wu, F. (2016). Underwater sensor network redeployment algorithm based on wolf search. Sensors, 16(10), 1754.
Liu, J., Jiang, P., Wu, F., Yu, S., & Song, C. (2017). Node redeployment algorithm based on stratified connected tree for underwater sensor networks. Sensors, 17(1), 27.
Fan, X., Hao, X., Cheng, S., & Yan, T. (2018). Node redeployment for 3D barrier coverage in underwater sensor networks. Chinese Journal of Sensors and Actuators, 31, 304–311. https://doi.org/10.3969/j.issn.1004-1699.2018.02.025
Jiang, P., Wang, X., & Liu, J. (2018). A sensor redeployment algorithm based on virtual forces for underwater sensor networks. Chinese Journal of Electronics, 27(2), 413–421.
Liu, C., Zhao, Z., Qu, W., Qiu, T., & Kumar Sangaiah, A. K. (2019). A distributed node deployment algorithm for underwater wireless sensor networks based on virtual forces. Journal of Systems Architecture, 97, 9–19.
Liu, f., L., Liu, C., Shu, Y and Ma, M., (2018). Optimal relay node placement for connectivity recovery in underwater acoustic sensor networks. In 2018 IEEE International Conference on Information Communication and Signal Processing (ICICSP), IEEE, (pp. 33–37).
Nandhini, E., & Senthilkumar, V. (2018). On energy hole and coverage hole avoidance in underwater wireless sensor networks using ABC algorithm. IJARCCE, International Journal of Advanced Research in Computer and Communication Engineering. https://doi.org/10.17148/IJARCCE.2018.735
Zhao, X., Cui, Y.-P., Gao, C.-Y., Guo, Z., & Gao, Q. (2019). Energy-efficient coverage enhancement strategy for three-dimensional wireless sensor networks based on a vampire bat optimizer. IEEE Internet of Things Journal., 7(1), 325–338.
Dhiman, G., & Kumar, V. (2018). Emperor penguin optimizer: A bio-inspired algorithm for engineering problems. Knowledge-Based Systems, 159, 20–50.
Wang, H., Li, K., & Pedrycz, W. (2020). An elite hybrid metaheuristic optimization algorithm for maximizing wireless sensor networks lifetime with a sink node. IEEE Sensors Journal, 20(10), 5634–5649.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Gupta, B., Gola, K.K. & Dhingra, M. HEPSO: an efficient sensor node redeployment strategy based on hybrid optimization algorithm in UWASN. Wireless Netw 27, 2365–2381 (2021). https://doi.org/10.1007/s11276-021-02584-4
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11276-021-02584-4