Abstract
In the majority of wireless sensor network applications, location information is crucial. Numerous localization techniques have been presented in recent years, the majority of them are oriented at two-dimensional applications. Whereas the challenge is more complicated in three-dimensional systems due to the broad range of altitude levels. For these purposes, two-dimensional localization models are unreliable. In this research, we use only one anchor node to identify the location of unknown sensors in a three-dimensional scenario utilizing both range-based and range-free strategies (with fuzzy logic). The middle and lower layers include sensor nodes with uncertain positions, whereas the top layer contains an anchor node. These heterogeneous mobile target nodes are deployed in an anisotropic environment having Degree of Irregularity of 0.01. The simulation results demonstrate that range-based localization techniques are significantly more efficient than range-free techniques by applying a new Adaptive SSA technique and other meta-heuristic algorithms to compute the results of range-based and range-free techniques in terms of localization error, computational time, and number of localized sensor nodes.
Similar content being viewed by others
References
Yang, X.-S. Firefly algorithm, stochastic test functions and design optimization. arXiv preprint. arXiv:1003.1409.
Arampatzis, T., Lygeros, J., Manesis, S. (2005). A survey of applications of wireless sensors and wireless sensor networks. In Proceedings of the 2005 IEEE International Symposium on, Mediterrean Conference on Control and Automation Intelligent Control, pp. 719–724.
Rongbai, Z., Guohua, C. (2010). Research on major hazard installations monitoring system based on wsn, In 2nd International Conference on Future Computer and Communication, 1, V1–741.
Ghelardoni, L., Ghio, A., Anguita, D. (2012). Smart underwater wireless sensor networks. In IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEE, pp. 1–5.
Zhou, Y., Ao, X., Xia, S. (2008). An improved APIT node self-localization algorithm in WSN. In 7th World Congress on Intelligent Control and Automation (WCICA 2008), pp. 7582–7586.
Bachrach, J., Taylor, C. (2005). Localization in sensor networks. In Handbook of Sensor Networks. 277–310.
Gao, G., Lei, L. (2010). An improved node localization algorithm based on DV-HOP in WSN. In 2nd International Conference on Advanced Computer Control (ICACC), 4, 321–324.
Doherty, L., & El Ghaoui, L. (2001). Convex position estimation in wireless sensor networks. Proceeding of INFOCOM, 3, 1655–1663.
Teng, R., & Zhang, B. (2010). On-demand information retrieval in sensor networks with localised query and energy-balanced data collection. Sensors, 11(1), 341–361.
Bulusu, N., Heidemann, J., & Estrin, D. (2000). GPS-less low-cost outdoor localization for very small devices. IEEE Personal Communications, 7(5), 28–34.
Graefenstein, J., Albert, A., Biber, P., Schilling, A. (2009). Wireless node localization based on RSSI using a rotating antenna on a mobile robot. In 6th Workshop on Positioning, Navigation and Communication (pp. 253–259). Hannover, Germany: IEEE.
Sumathi, R., Srinivasan, R. (2011). RSS-based location estimation in mobility assisted wireless sensor networks. In 6th International Conference on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS) (vol. 2, pp. 848–852).
Guo, G.Z., Hong, Y., Jin, F., Feng, Y., & Liu, Y. (2010). Perpendicular intersection: locating wireless sensors with mobile beacon. IEEE Transactions on Vehicular Technology, 59(7), 3501–3509.
Wang, L., Zhang, J., Cao, D. (2012). A new 3-dimensional dv-hop localization algorithm. Journal of Computer Information Systems, 8(6), 2463–2475.
Xu, E., Ding, Z., & Dasgupta, S. (2011). Source localization in wireless sensor networks from signal time-of-arrival measurements. IEEE Transactions on Signal Processing, 59(6), 2887–2897.
Li, H., Wang, J., Li, X., Ma, H. (2008). Real-time path planning of mobile anchor node in localization for wireless sensor networks. In: International Conference on Information and Automation (pp. 384–389).
Ahmad, T., Li, X.J., Seet, B.C. (2017). Parametric loop division for 3d localization in wireless sensor networks. Sensors, 17(7), 1–20.
Gopakumar, A., Lillykutty, J. (2008) Localization in wireless sensor networks using particle swarm optimization. Proceeding of IET International Conference on Wireless, Mobile and Multimedia Networks (pp. 227–230). IEEE.
Cheng, L., Wu, C.-D., Zhang, Y.-Z. (2011). Indoor robot localization based on wireless sensor networks. IEEE Transactions on Consumer Electronics, 57(3).
Kulkarni, R.V., Venayagamoorthy, G.K., Cheng, M.X. (2009). Bio-inspired node localization in wireless sensor networks. In Proceeding of IEEE International Conference on Systems, Man and Cybernetics (pp. 205–210). IEEE.
Kumar, A., Singh, K. (2015). Optimized range-free 3D node localization in wireless sensor networks using firefly algorithm. In Proceeding of International conference on Signal Processing and Communication (pp. 14–19). IEEE.
Arora, S., Singh, S. (2017). Node localization in wireless sensor networks using butterfly optimization algorithm. Arabian Journal for Science and Engineering, 42(8), 3325–3335.
Zhang, B., Fan, J., Dai, G., & Luan, T. H. (2015). A hybrid localization approach in 3d wireless sensor network. International Journal of Distributed Sensor Networks, 2014, 1–11.
Xiong, H., & Sichitiu, M. L. (2019). A lightweight localization solution for small, low resources wsns. Journal of Sensor and Actuator Networks, 8(2), 1–26.
Sivasakthiselvan, S., & Nagarajan, V. (2019). A new localization technique for node positioning in wireless sensor networks. Cluster Computing, 22(2), 4027–4034.
Chen, H., & Tan, G. (2019). Adaptive iteration localization algorithm based on rssi in wireless sensor networks. Cluster Computing, 22(2), 3059–3067.
Nguyen, T.L.N, Vy, T. D., & Shin, Y. (2019). An efficient hybrid rss-aoa localization for 3d wireless sensor networks. Sensors, 19(9), 1–20.
Kumar, A., Khosla, A., Saini, J. S., & Sidhu, S. S. (2015). Range-free 3d node localization in anisotropic wireless sensor networks. Applied Soft Computing, 34, 438–448.
Sharma, G., & Kumar, A. (2018). Fuzzy logic based 3d localization in wireless sensor networks using invasive weed and bacterial foraging optimization. Telecommunication Systems, 67(2), 149–162.
Lee, S., Park, C., Lee, M. J., & Kim, S. (2014). Multihop range-free localization with approximate shortest path in anisotropic wireless sensor networks. EURASIP Journal on Wireless Communications and Networking, 1–20.
Chen, Y.-S., Ting, Y.-J., Ke, C.-H., Chilamkruti, N., & Park, J. H. (2013). Efficient localization scheme with ring overlapping by utilizing mobile anchors in wireless sensor networks. ACM Transactions on Embedded Computing Systems (TECS), 12(2), 1–18.
Chaurasiya, V. K., Jain, N., & Nandi, G. C. (2014). A novel distance estimation approach for 3d localization in wireless sensor network using multidimensional scaling. Information Fusion, 15, 5–18.
Zhang, X., Wang, T., & Fang, J. (2014). A node localization approach using particle swarm optimization in wireless sensor networks. In International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI) (pp. 84–87).
Mirjalili, S., Gandomi, A. H., Mirjalili, S. Z., Saremi, S., Faris, H., & Mirjalili, S. M. (2017). Salp swarm algorithm: A bio-inspired optimizer for engineering design problems. Advances in Engineering Software, 114, 163–191.
Chen, T., Wang, M., Huang, X., & Xie, Q. (2018). Tdoa-aoa localization based on improved salp swarm algorithm. In 2018 14th IEEE International Conference on Signal Processing (ICSP) (pp. 108–112). IEEE.
Qais, M. H., Hasanien, H. M., & Alghuwainem, S. (2019). Enhanced salp swarm algorithm: Application to variable speed wind generators. Engineering Applications of Artificial Intelligence, 80, 82–96.
Li, S., Yu, Y., Sugiyama, D., Li, Q. & Gao, S. (2018). A hybrid salp swarm algorithm with gravitational search mechanism. In 2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS) (pp. 257–261). IEEE.
Salgotra, R., Singh, U., Singh, S., Singh, G., & Mittal, N. (2021). Self-adaptive salp swarm algorithm for engineering optimization problems. Applied Mathematical Modelling, 89(1), 188–207.
Mirjalili, S., Mirjalili, S. M., & Lewis, A. (2014). Grey wolf optimizer. Advances in Engineering Software, 69, 46–61.
Yang, X.-S., & Deb, S. (2010). Engineering optimisation by cuckoo search. International Journal of Mathematical Modelling and Numerical Optimisation, 1(4), 330–343.
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
Singh, P., Mittal, N. & Salgotra, R. Comparison of range-based versus range-free WSNs localization using adaptive SSA algorithm. Wireless Netw 28, 1625–1647 (2022). https://doi.org/10.1007/s11276-022-02908-y
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11276-022-02908-y