Generic placeholder image

International Journal of Sensors, Wireless Communications and Control

Editor-in-Chief

ISSN (Print): 2210-3279
ISSN (Online): 2210-3287

Research Article

A Novel Polytope Algorithm based On Nelder-mead Method for Localization in Wireless Sensor Network

Author(s): Bassam Gumaida* and Adamu Abubakar Ibrahim

Volume 14, Issue 1, 2024

Published on: 03 January, 2024

Page: [21 - 35] Pages: 15

DOI: 10.2174/0122103279270847231205100550

Price: $65

conference banner
Abstract

Background and Objectives: Magnificent localization precision and low operating expenses are the main keys and essential issues to managing and operating outdoor wireless sensor networks. This work proposes a novel and rigorous efficiency localization algorithm utilizing a simplex optimization approach for node localization. This novel optimization method is a direct search approach, and is usually directed to solve nonlinear optimization problems that may not have wellknown derivatives, and it is called the Nelder-mead Method (NMM).

Methods: It is suggested that the objective function that will be optimized using NMM is the mean squared error of the range of all neighboring anchor nodes installed in the studied WSNs. This paper emphasizes employing a ranging technique called Received Signal Strength Indicator (shortly RSSI) to calculate the length of distances among all the nodes of WSNs.

Results: Simulation results perfectly showed that the suggested localization algorithm based on NMM can carry out a better performance than that of other localization algorithms utilizing other optimization approaches, including a particle swarm optimization, ant colony (ACO) and bat algorithm (BA). This obviously appeared in several metrics of performance evaluation, such as accuracy of localization, node localization rate, and implementation time.

Conclusion: The proposed algorithm that utilized NMM is more functional to enhance the precision of localization because of particular characteristics that are the flexible implementation of NMM and the free cost of using the RSSI technique.

Keywords: Wireless sensor networks, ranging model, RSSI, optimization techniques, nelder mead method, localization.

Graphical Abstract
[1]
Aggarwal N, Sharma N, Bhale Y. Performance analysis of power efficient routing protocols for wireless sensor networks: A survey 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE).
[http://dx.doi.org/10.1109/ICACITE53722.2022.9823426]
[2]
Singh S, Shivangna S, Mittal E. Range based wireless sensor node localization using PSO and BBO and its variants 2013 Int Conf Commun Syst Netw Technol. 309-15.
[http://dx.doi.org/10.1109/CSNT.2013.72]
[3]
Gumaida BF, Luo J. Novel localization algorithm for wireless sensor network based on intelligent water drops. Wirel Netw 2017; (11): 1-13.
[4]
Hu J, Luo J, Zhang Y, Wang P, Liu Y. Location-based data aggregation in 6LoWPAN. Int J Distrib Sens Netw 2015; 2015(4): 1-9.
[http://dx.doi.org/10.1155/2015/912926]
[5]
Marks M, Niewiadomska-szynkiewicz E. Self-adaptive localization using signal strength measurements.
[6]
Luo J, Hu J, Wu D, Li R. Opportunistic routing algorithm for relay node selection in wireless sensor networks. IEEE Trans Industr Inform 2015; 11(1): 112-21.
[http://dx.doi.org/10.1109/TII.2014.2374071]
[7]
Goyal KN. An optimal scheme for minimizing energy consumption in WSN. Glob Res Dev J Eng 2016; 1: 1-7.
[8]
Nain M, Goyal N. Energy efficient localization through node mobility and propagation delay prediction in underwater wireless sensor network. Wirel Pers Commun 2022; 122(3): 2667-85.
[http://dx.doi.org/10.1007/s11277-021-09024-8]
[9]
Nithya B, Jeyachidra J. Optimized anchor based localization using bat optimization algorithm for heterogeneous WSN 2021 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES). 1-6.
[http://dx.doi.org/10.1109/ICSES52305.2021.9633947]
[10]
Xiao F, Wu M, Huang H, Wang R, Wang S. Novel node localization algorithm based on nonlinear weighting least square for wireless sensor networks. Int J Distrib Sens Netw 2012; 8(11): 803840.
[http://dx.doi.org/10.1155/2012/803840]
[11]
Cao W, Wang H, Liu L. An ant colony optimization algorithm for virtual network embedding. ICA3PP 2014: Algorithms and Architectures for Parallel Processing 4(3): 299-309.
[12]
Malhotra R, Singh N, Singh Y. Genetic algorithms: Concepts. design for optimization of process controllers 2011; 4(2): 39-54.
[13]
Cao W, Wang H, Liu L. A comparative analysis of localization techniques in wireless sensor network. 2022 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES)
[http://dx.doi.org/10.1109/SPICES52834.2022.9774208]
[14]
Kagi S, Mathapati BS. Localization in wireless sensor networks: A compact review on state-of-the-Art models. 2021 6th International Conference on Inventive Computation Technologies (ICICT)
[http://dx.doi.org/10.1109/ICICT50816.2021.9358793]
[15]
Arampatzis T, Lygeros J, Manesis S. A survey of applications of wireless sensors and wireless sensor networks. Proceedings of the 2005 IEEE International Symposium on, Mediterrean Conference on Control and Automation Intelligent Control
[http://dx.doi.org/10.1109/.2005.1467103]
[16]
Amundson I, Koutsoukos X. A survey on localization for mobile wireless sensor networks. Mob. Entity Localization Track 2009; pp. 235-54.
[http://dx.doi.org/10.1007/978-3-642-04385-7_16]
[17]
Mao G, Fidan B, Anderson BDO. Wireless sensor network localization techniques. Comput Netw 2007; 51(10): 2529-53.
[http://dx.doi.org/10.1016/j.comnet.2006.11.018]
[18]
Yick J, Mukherjee B, Ghosal D, Mukherjee B, Ghosal D. Wireless sensor network survey. Comput Netw 2008; 52(12): 2292-330.
[http://dx.doi.org/10.1016/j.comnet.2008.04.002]
[19]
Rawat P, Singh KD, Chaouchi H, Bonnin JM. Wireless sensor networks: A survey on recent developments and potential synergies. J Supercomput 2014; 68(1): 1-48.
[http://dx.doi.org/10.1007/s11227-013-1021-9]
[20]
Gupta O, Goyal N. The evolution of data gathering static and mobility models in underwater wireless sensor networks: A survey. J Ambient Intell Humaniz Comput 2021; 12(10): 9757-73.
[http://dx.doi.org/10.1007/s12652-020-02719-z]
[21]
Lu YH, Zhang M. Adaptive mobile anchor localization algorithm based on ant colony optimization in wireless. Int J Smart Sensing Intell Syst 2014; 7(4): 1943-61.
[http://dx.doi.org/10.21307/ijssis-2017-741]
[22]
Uraiya K, Gandhi DK. Genetic algorithm for wireless sensor network with localization based techniques. Int J Sci Res Publ 2014; 4(9): 1-6.
[23]
Cheng Q. A robust indoor localization algorithm for WSN in LOS and NLOS environment. 2021 IEEE 11th International Conference on Electronics Information and Emergency Communication (ICEIEC) 2021 IEEE 11th International Conference on Electronics Information and Emergency Communication (ICEIEC)
[http://dx.doi.org/10.1109/ICEIEC51955.2021.9463824]
[24]
Rayavarapu VCSR, Mahapatro A. A novel range-free anchor-free localization.WSN Using Sun Flower Optimization Algorithm,” in 2021 Advanced Communication Technologies and Signal Processing. ACTS 2021; pp. 1-6.
[http://dx.doi.org/10.1109/ACTS53447.2021.9708099]
[25]
Rosić MB, Simić MI, Pejović PV. Passive target localization problem based on improved hybrid adaptive differential evolution and Nelder-Mead algorithm. J Sens 2020; 2020: 1-20.
[http://dx.doi.org/10.1155/2020/3482463]
[26]
Tagne Fute E, Nyabeye Pangop DK, Tonye E. A new hybrid localization approach in wireless sensor networks based on particle swarm optimization and tabu search. Appl Intell 2023; 53(7): 7546-61.
[http://dx.doi.org/10.1007/s10489-022-03872-y]
[27]
Yang Q. A new localization method based on improved particle swarm optimization for wireless sensor networks. IET Softw 2022; 16(3): 251-8.
[http://dx.doi.org/10.1049/sfw2.12027]
[28]
Tariq SM, Al-Mejibli IS. WSN localization method based on hybrid PSO-GRNN approach. Int J Intell Eng Syst 2023; 16(5)
[29]
Mohanta TK, Das DK. Improved wireless sensor network localization algorithm based on selective opposition class topper optimization (SOCTO). Wirel Pers Commun 2023; 128(4): 2847-68.
[http://dx.doi.org/10.1007/s11277-022-10075-8]
[30]
Jacob L. Localization in wireless sensor networks using particle swarm optimization. IET Conf Proc 2008; (3): 227-30.
[31]
Zhang F. Positioning research for wireless sensor networks based on PSO algorithm 2013; (20220744): 7-10.
[32]
CHUANG P. Employing PSO to enhance RSS range-based node local-ization for wireless sensor networks. J Inf Sci 2011; 1611: 1597-611.
[33]
Low KS. A particle swarm optimization approach for the localization of a wireless sensor network 2008 IEEE Int Symp Ind Electron. 1820-5.
[http://dx.doi.org/10.1109/ISIE.2008.4677205]
[34]
Low KS, Nguyen HA, Guo H. Optimization of sensor node locations in a wireless sensor network. 2008 Fourth Int Conf Nat Comput 2008; 5: 286-90.
[http://dx.doi.org/10.1109/ICNC.2008.670]
[35]
Kulkarni RV, Venayagamoorthy GK. Particle swarm optimization in wireless-sensor networks: A brief survey In: IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) ( Volume: 41, Issue: 2, March 2011). 2011.
[http://dx.doi.org/10.1109/TSMCC.2010.2054080]
[36]
Al Alawi R. RSSI based location estimation in wireless sensors networks. 2011; pp. 118-22.
[http://dx.doi.org/10.1109/ICON.2011.6168517]
[37]
McKinnon KIM. Convergence of the nelder-mead simplex method to a non-stationary point. SIAM J Optim 1998; 9(1): 148-58.
[http://dx.doi.org/10.1137/S1052623496303482]
[38]
Lewis RM, Shepherd A, Torczon V. Implementing generating set search methods for linearly constrained minimization. SIAM J Sci Comput 2007; 29(6): 2507-30.
[http://dx.doi.org/10.1137/050635432]
[39]
Nelder JA, Mead R. A simplex method for function minimization comput. Comput J 1965; (4): 4.
[40]
Addelman S. Designs for the sequential application of factors. Technometrics 1964; 6(4): 365-70.
[http://dx.doi.org/10.1080/00401706.1964.10490200]
[41]
Ricardo S, Broderick C, Cristian G, Eric M, Fernando P. A prefiltered cuckoo search algorithm with geometric operators for solving sudoku problems. The Scientific World Journal 2014; 2014(4): 465359.

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy