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An analytical framework for centroid-based localization in wireless sensor networks

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Abstract

The centroid of a set of points can be used by a sensor to compute its location provided that each point represents an anchor with a known location. In this paper, we present mathematical characteristics of centroid based localization in a wireless sensor network. We prove that the centroid of a set of points minimizes an objective function, which is the summation of squares of distances from individual points. We provide a mathematical expression for the minimum value of the summation of the objective function. Also, we provide an expression for the distance between the centroids of a set of k and \((k+1)\) points. We describe a scheme for localization of sensors using the centroid of locations of anchors. Our scheme excludes locations of anchors that may adversely affect localization of a sensor.

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References

  1. Abbas AM (2020) Analysis of error for anchor-based localization in wireless sensor networks. J Interdiscip Math 23(2):393–401. https://doi.org/10.1080/09720502.2020.1731952

    Article  Google Scholar 

  2. Abbas AM, Qasem HAAR (2017) Virp: virtual points based localization scheme for wireless sensor networks. Wireless Pers Commun 97(2):2951–2970. https://doi.org/10.1007/s11277-017-4644-y

    Article  Google Scholar 

  3. Alagha A, Singh S, Otrok H, Mizouni R (2020) Rfls - resilient fault-proof localization system in iot and crowd-based sensing applications. J Netw Comput Appl 170:102783. https://doi.org/10.1016/j.jnca.2020.102783

    Article  Google Scholar 

  4. Behnad A, Wang X, Hanzo L, Willink TJ (2018) Connectivity-based centroid localization using distributed dense reference nodes. IEEE Trans Veh Technol 67(7):6685–6689. https://doi.org/10.1109/TVT.2018.2806198

    Article  Google Scholar 

  5. Bulusu N, Heidemann J, Estrin D (2000) Gps-less low-cost outdoor localization for very small devices. IEEE Pers Commun 7(5):28–34. https://doi.org/10.1109/98.878533

    Article  Google Scholar 

  6. Chen H, Huang P, Martins M, So HC, Sezaki K (2008) Novel centroid localization algorithm for three-dimensional wireless sensor networks. In: IEEE 4th International conference on wireless communications, networking and mobile computing (WiCOM), pp 1–4. https://doi.org/10.1109/WiCom.2008.841

  7. Chen T, Sun L, Wang Z, Wang Y, Zhao Z, Zhao P (2021) An enhanced nonlinear iterative localization algorithm for dv\_hop with uniform calculation criterion. Ad Hoc Netw 111:102327. https://doi.org/10.1016/j.adhoc.2020.102327

    Article  Google Scholar 

  8. Dou L, Song C, Wang X, Liu L, Feng G (2020) Target localization and enclosing control for networked mobile agents with bearing measurements. Automatica 118:109022. https://doi.org/10.1016/j.automatica.2020.109022

    Article  MathSciNet  MATH  Google Scholar 

  9. El Khediri S, Fakhet W, Moulahi T, Khan R, Thaljaoui A, Kachouri A (2020) Improved node localization using k-means clustering for wireless sensor networks. Comput Sci Rev 37:100284. https://doi.org/10.1016/j.cosrev.2020.100284

    Article  MathSciNet  MATH  Google Scholar 

  10. Gao Z, Guo H, Xie Y, Lu H, Zhang J, Diao W, Xu R (2020) An improved localization method in cyber-social environments with obstacles. Comput Electr Eng 86:106694. https://doi.org/10.1016/j.compeleceng.2020.106694

    Article  Google Scholar 

  11. Janssen T, Berkvens R, Weyn M (2020) Benchmarking rss-based localization algorithms with lorawan. Int Things 11:100235. https://doi.org/10.1016/j.iot.2020.100235

    Article  Google Scholar 

  12. Jiang R, Wang X, Zhang L (2018) Localization algorithm based on iterative centroid estimation for wireless sensor networks. Math Probl Eng 2018:1–11. https://doi.org/10.1155/2018/5456191

    Article  Google Scholar 

  13. Liu Z, Hu D, Zhao Y, Zhao Y (2020) Computationally efficient tdoa, fdoa and differential doppler rate estimation algorithm for passive emitter localization. Digit Signal Process 96:102598. https://doi.org/10.1016/j.dsp.2019.102598

    Article  Google Scholar 

  14. Oliveira LL, Dessbesell GF, Martins JB, Monteiro J (2011)Hardware implementation of a centroid-based localization algorithm for mobile sensor networks. In: IEEE international symposium of circuits and systems (ISCAS), pp. 2829–2832 . https://doi.org/10.1109/ISCAS.2011.5938194

  15. Oliveira LL, Martins JB, Dessbesell GF, Monteiro J (2010) Centroidm: a centroid-based localization algorithm for mobile sensor networks. In: Proceedings of the 23rd Symposium on Integrated Circuits and System Design (SBCCI), pp 204–209. Association for Computing Machinery, New York, NY. https://doi.org/10.1145/1854153.1854203

  16. Tu Q, Liu Y, Han F, Liu X, Xie Y (2021) Range-free localization using reliable anchor pair selection and quantum-behaved salp swarm algorithm for anisotropic wireless sensor networks. Ad Hoc Netw 113:102406. https://doi.org/10.1016/j.adhoc.2020.102406

    Article  Google Scholar 

  17. Wang D, Huang Q, Chen X, Ji L (2020) Location of three-dimensional movement for a human using a wearable multi-node instrument implemented by wireless body area networks. Comput Commun 153:34–41. https://doi.org/10.1016/j.comcom.2020.01.070

    Article  Google Scholar 

  18. Wang J, Hou A, Tu Y (2019) An improved dv-hop localization algorithm based on centroid multilateration. In: Proceedings of the ACM Turing Celebration Conference - China (TURC). Association for Computing Machinery, New York, NY. https://doi.org/10.1145/3321408.3326658

  19. Wang P, Tu G (2020) Localization algorithm of wireless sensor network based on matrix reconstruction. Comput Commun 154:216–222. https://doi.org/10.1016/j.comcom.2020.01.051

    Article  Google Scholar 

  20. Waqar A, Ahmad I, Habibi D, Phung QV (2021) Analysis of gps and uwb positioning system for athlete tracking. Measur Sens 14:100036. https://doi.org/10.1016/j.measen.2020.100036

  21. Xu H, Li Q, Wang J, Yang J, Sun W (2020) Cramer-rao lower bound analysis of rss/tdoa joint localization algorithms based on rigid graph theory. Ad Hoc Netw 103:102146. https://doi.org/10.1016/j.adhoc.2020.102146

    Article  Google Scholar 

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Correspondence to Ash Mohammad Abbas.

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Abbas, A.M. An analytical framework for centroid-based localization in wireless sensor networks. Int. j. inf. tecnol. 13, 1777–1783 (2021). https://doi.org/10.1007/s41870-021-00736-5

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