Abstract
The node localization problem of wireless sensor networks (WSNs) is addressed in this article with a node localization algorithm designed using fuzzy logic and a nature-inspired algorithm. The coordinates of target nodes are obtained using fuzzy logic reasoning and nature-inspired algorithms. The fuzzy logic concept is used to remove the nonlinearities that arise due to signal strength measurement in the process of range estimation. The triangular and trapezoidal membership functions are used with the Mamdani fuzzy inference system for distance improvement between sensor nodes. Further, particle swarm optimization (PSO) and the Jaya algorithm (JA) determine the target nodes’ location coordinates. The comparison of the proposed fuzzy logic-based PSO (FL-PSO) and fuzzy logic-based JA (FL-JA) algorithms is made with PSO and Jaya algorithm-based node localization algorithms for localization error. The influence of anchor nodes and degree of irregularity is verified during localization analysis on the FL-PSO and FL-JA node localization algorithms. The proposed FL-PSO and FL-JA node localization algorithms are evaluated for scalability, computation time, mean absolute deviation, and complexity to determine their efficacy. The simulations are carried out on MATLAB software in addition to the fuzzy logic toolbox.













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References
Bhowmik S, Giri C (2013) A novel fuzzy sensing model for sensor nodes in wireless sensor network. In: Intelligent Informatics, pp 365–371. Springer
Bhowmik S, Giri C (2016) A fuzzy communication model of sensor nodes in wireless sensor network. Int J Sensor Netw 21(1):1–15
Saha S, Arya R (2022) Arcmt: Anchor node-based range free cooperative multi trusted secure underwater localization using fuzzifier. Comput Commun 193:246–265
Giri A, Dutta S, Neogy S (2020) Fuzzy logic-based range-free localization for wireless sensor networks in agriculture. In: Advanced Computing and Systems for Security, pp 3–12. Springer
Sharma G, Kumar A, Singh P, Hafeez MJ (2018) Localization in wireless sensor networks using invasive weed optimization based on fuzzy logic system. In: Advanced Computing and Communication Technologies, pp 245–255. Springer
Parulpreet S, Arun K, Anil K, Mamta K (2019) Computational intelligence techniques for localization in static and dynamic wireless sensor networks—a review. Comput Intell Sensor Netw, 25–54
Yun S, Lee J, Chung W, Kim E, Kim S (2009) A soft computing approach to localization in wireless sensor networks. Expert Syst Appl 36(4):7552–7561
So-In C, Permpol S, Rujirakul K (2016) Soft computing-based localizations in wireless sensor networks. Pervasive Mob Comput 29:17–37
Bhowmik S, Kar R, Giri C (2016) Fuzzy node localization in wireless sensor network. In: 2016 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), pp 1112–1116. IEEE
Kumar S, Lobiyal D (2017) Novel dv-hop localization algorithm for wireless sensor networks. Telecommun Syst 64(3):509–524
Mehrabi M, Taheri H, Taghdiri P (2017) An improved dv-hop localization algorithm based on evolutionary algorithms. Telecommun Syst 64(4):639–647
Phoemphon S, So-In C, Leelathakul N (2018) Optimized hop angle relativity for dv-hop localization in wireless sensor networks. IEEE Access 6:78149–78172
Sharma G, Kumar A (2018) Improved dv-hop localization algorithm using teaching learning based optimization for wireless sensor networks. Telecommun Syst 67(2):163–178
Phoemphon S, So-In C, Nguyen TG (2018) An enhanced wireless sensor network localization scheme for radio irregularity models using hybrid fuzzy deep extreme learning machines. Wireless Netw 24(3):799–819
Phoemphon S, So-In C, Leelathakul N (2018) Fuzzy weighted centroid localization with virtual node approximation in wireless sensor networks. IEEE Internet Things J 5(6):4728–4752
Sharma G, Kumar A (2018) Fuzzy logic based 3d localization in wireless sensor networks using invasive weed and bacterial foraging optimization. Telecommun Syst 67(2):149–162
Amri S, Khelifi F, Bradai A, Rachedi A, Kaddachi ML, Atri M (2019) A new fuzzy logic based node localization mechanism for wireless sensor networks. Futur Gener Comput Syst 93:799–813
Cheng L, Hang J, Wang Y, Bi Y (2019) A fuzzy c-means and hierarchical voting based rssi quantify localization method for wireless sensor network. IEEE Access 7:47411–47422
Mohar SS, Goyal S, Kaur R (2022) Optimum deployment of sensor nodes in wireless sensor network using hybrid fruit fly optimization algorithm and bat optimization algorithm for 3d environment. Peer-to-Peer Netw Appl 15(6):2694–2718
Phoemphon S, So-In C, Leelathakul N (2021) Improved distance estimation with node selection localization and particle swarm optimization for obstacle-aware wireless sensor networks. Expert Syst Appl 175:114773
Mohanta TK, Das DK (2022) Advanced localization algorithm for wireless sensor networks using fractional order class topper optimization. J Supercomput 78(8):10405–10433
Shilpi, Gautam PR, Kumar S, Kumar A (2022) An optimized sensor node localization approach for wireless sensor networks using rssi. J Supercomput, 1–25
Ou X, Wu M, Pu Y, Tu B, Zhang G, Xu Z (2022) Cuckoo search algorithm with fuzzy logic and gauss-cauchy for minimizing localization error of wsn. Appl Soft Comput 125:109211
Rani AJM, Pravin A (2019) Multi-objective hybrid fuzzified pso and fuzzy c-means algorithm for clustering cdr data. In: 2019 International Conference on Communication and Signal Processing (ICCSP), pp 0094–0098. IEEE
Verma A, Kumar S, Gautam PR, Rashid T, Kumar A (2020) Fuzzy logic based effective clustering of homogeneous wireless sensor networks for mobile sink. IEEE Sens J 20(10):5615–5623
Srivastava A, Prakash A, Tripathi R (2020) Fuzzy-based beaconless probabilistic broadcasting for information dissemination in urban vanet. Ad Hoc Netw 108:102285
Rajan MS, Dilip G, Kannan N, Namratha M, Majji S, Mohapatra SK, Patnala TR, Karanam SR (2021) Diagnosis of fault node in wireless sensor networks using adaptive neuro-fuzzy inference system. Appl Nanosci, 1–9
Mohar SS, Goyal S, Kaur R (2023) Exploration of different topologies for optimal sensor nodes deployment in wireless sensor networks using jaya-sine cosine optimization algorithm. J Supercomput 79(12):13001–13030
Phoemphon S, So-In C, Aimtongkham P, Nguyen TG (2021) An energy-efficient fuzzy-based scheme for unequal multihop clustering in wireless sensor networks. J Ambient Intell Hum Comput 12(1):873–895
Jayaraman G, Dhulipala V (2022) Feecs: Fuzzy-based energy-efficient cluster head selection algorithm for lifetime enhancement of wireless sensor networks. Arab J Sci Eng 47(2):1631–1641
Nain M, Goyal N, Awasthi LK, Malik A (2022) A range based node localization scheme with hybrid optimization for underwater wireless sensor network. Int J Commun Syst, 5147
Mohar SS, Goyal S, Kaur R (2022) Localization of sensor nodes in wireless sensor networks using bat optimization algorithm with enhanced exploration and exploitation characteristics. J Supercomput 78(9):11975–12023
Yadav P, Sharma SC, Singh O, Rishiwal V (2023) Optimized localization learning algorithm for indoor and outdoor localization system in wsns. Wireless Pers Commun 130(1):651–672
Álvarez R, Díez-González J, Verde P, Ferrero-Guillén R, Perez H (2023) Combined sensor selection and node location optimization for reducing the localization uncertainties in wireless sensor networks. Ad Hoc Netw 139:103036
Mohan Y, Yadav RK, Manjul M (2024) Seagull optimization algorithm for node localization in wireless sensor networks. Multimedia Tools Appl, 1–22
Rawat P, Kumar P, Chauhan S (2023) Fuzzy logic and particle swarm optimization-based clustering protocol in wireless sensor network. Soft Comput 27(9):5177–5193
Rao RV, Rai D, Ramkumar J, Balic J (2016) A new multi-objective jaya algorithm for optimization of modern machining processes. Adv Prod Eng Manag 11(4)
Shilpi, Kumar A (2023) A localization algorithm using reliable anchor pair selection and jaya algorithm for wireless sensor networks. Telecommun Syst, 1–13
Houssein EH, Gad AG, Wazery YM (2021) Jaya algorithm and applications: a comprehensive review. Metaheuristics Optim Comput Electr Eng, 3–24
Zitar RA, Al-Betar MA, Awadallah MA, Doush IA, Assaleh K (2022) An intensive and comprehensive overview of jaya algorithm, its versions and applications. Arch Comput Methods Eng 29(2):763–792
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Shilpi designed and analyzed the proposed algorithm using simulations under the supervision of Arvind Kumar. She wrote the manuscript in consultation with him.
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Shilpi, Kumar, A. Sensor node localization using nature-inspired algorithms with fuzzy logic in WSNs. J Supercomput 80, 26776–26804 (2024). https://doi.org/10.1007/s11227-024-06464-4
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DOI: https://doi.org/10.1007/s11227-024-06464-4