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Auto-localization algorithm for mobile sensor nodes in wireless sensor networks

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Abstract

In wireless sensor networks, location information is crucial to effectively use the event information recorded by the sensors. However, localizing mobile sensor nodes in resource-constrained networks presents several challenges, including determining the optimal number of anchor nodes, handling mobility, designing a path loss model, considering network topology, and addressing scalability and the number of localized nodes. To overcome these challenges, this paper proposes a coordinate-based auto-localization algorithm (CALA) with a single anchor node for mobile sensor nodes. The proposed algorithm uses an analytical model to determine the location of the target node by considering a parallel coordinate system and retrieving the original location of the target node by moving it to two different locations. The algorithm uses received signal strength indicator (RSSI) values for distance calculation while considering Rayleigh fading in the path loss model. The proposed algorithm’s performance is evaluated using various parameter settings, including mobility, node density, fading, path loss exponent, and different random seed values. The study finds that fading and path loss significantly influence the localization process, leading to an accuracy range of 10 to 30% when measuring distances using RSSI. The proposed method shows a 30% improvement in localization accuracy when the number of nodes increases from 5 to 20, achieving an average localization accuracy of 90% in a network with 20 sensor nodes. Furthermore, the study offers an in-depth investigation of the effect of various random generating situations on localization accuracy. Overall, the proposed algorithm offers a promising solution to the challenges of localizing mobile sensor nodes in resource-constrained networks.

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References

  1. Wang C, Xiao L (2008) Sensor localization in concave environments. ACM Trans Sens Netw. https://doi.org/10.1145/1325651.1325654

    Article  Google Scholar 

  2. Paul AK, Sato T (2017) Localization in WSNs: a survey on algorithms, measurement techniques, applications and challenges. J Sens Actuator Netw 6:24. https://doi.org/10.3390/jsan6040024

    Article  Google Scholar 

  3. Musa A, Gonzalez V, Barragan D (2019) A new strategy to optimize the sensors placement in WSNs. J Ambient Intell Humaniz Comput 10(4):1389–1399. https://doi.org/10.1007/s12652-018-0868-2

    Article  Google Scholar 

  4. Chen S, Zhang J, Mao Y, Xu C, Gu Y (2019) Efficient distributed method for NLOS cooperative localization in WSNs. Sensors 19(5):1173. https://doi.org/10.3390/s19051173

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  5. Bhat SJ, Santhosh KV (2022) Localization of isotropic and anisotropic WSNs in 2D and 3D fields. Telecommun Syst 79:309–321. https://doi.org/10.1007/s11235-021-00862-2

    Article  Google Scholar 

  6. Lita I et al (2006) A new approach of automobile localization system using GPS and GSM/GPRS transmission. International Spring Seminar on Electronics Technology

  7. Stoleru R et al (2004) Walking GPS: A practical solution for localization in manually deployed WSNs. In: IEEE International Conference on Local Computer Networks

  8. Stefano P, Pascucci F, Ulivi G (2002) An outdoor navigation system using GPS and inertial platform. In: IEEE/ASME Transactions on Mechatronics

  9. Parkinson B et al (1996) Global positioning system: theory and application. Progress in Astronautics and Aeronautics, vol I

  10. Chowdhury T, Elkin C, Devabhaktuni V, Rawat DB, Oluoch J (2016) Advances on localization techniques for WSNs. Comput Netw 110:284–305

    Article  Google Scholar 

  11. Halder S, Ghosal A (2016) A survey on mobile anchor assisted localization techniques in WSNs. Wirel Netw 22:2317–2336

    Article  Google Scholar 

  12. Kuriakose J, Joshi S, Vikram Raju R, Kilaru A (2014) A review on localization in WSNs advances in signal processing 599 and intelligent recognition systems. Adv Intell Syst Comput. https://doi.org/10.1007/978-3-319-04960-1_52

    Article  Google Scholar 

  13. Mao G, Anderson BDO, Fidan B (2007) PLE estimation for WSN localization. Comput Netw 51:2467–2483

    Article  Google Scholar 

  14. Moses R, Krishnamurthy D, Patterson R (2003) A self-localization method for WSNs. EURASIP J Appl Signal Process, Special Issue on Sensor Networks

  15. Sarigiannidis G (2006) Localization for ad hoc WSNs. M.S. thesis, Technical University Delft, The Netherlands

  16. Xiao J, Ren L, Tan J (2006) Research of TDOA based self-localization approach in WSN. In: Proceedings IEEE/RSJ International Conference on Intelligent Robots and Systems

  17. Stoleru R, Stankovic J (2004) Probability grid: a location estimation scheme for WSNs. In: Proceedings of Sensor and Ad-Hoc Comm. And Networks Conference (SECON)

  18. Niculescu D, Nath B (2001) Ad hoc positioning system (APS). In: Proceedings of the IEEE Global Telecommunications Conference

  19. Han G, Xu H, Duong TQ, Jiang J, Hara T (2013) Localization algorithms of WSNs: a survey. Telecommun Syst 52(4):2419–2436

    Article  Google Scholar 

  20. Kaur A, Gupta GP, Mittal S (2022) Comparative study of the different variants of the DV-Hop based node localization algorithms for WSNs. Wirel Pers Commun 123:1625–1667. https://doi.org/10.1007/s11277-021-09206-4

    Article  Google Scholar 

  21. Fang Z, Zhao Z et al (2010) Localization in WSNs with Known Coordinate Database. EURASIP J Wirel Commun Netw

  22. Kulkarni VR (2023) Comparative analysis of static and mobile anchors in sensor localization. In: 2023 International Conference on Device Intelligence, Computing and Communication Technologies, (DICCT), Dehradun, India, pp 115–120 . https://doi.org/10.1109/DICCT56244.2023.10110135

  23. Chen Z (2021) Self-localization for mobile sensor networks with bearing measurements in local coordinate system. In: 2021 36th Youth Academic Annual Conference of Chinese Association of Automation (YAC), Nanchang, China, pp 150–155. https://doi.org/10.1109/YAC53711.2021.9486493.

  24. Bochem A, Zhang H (2022) Robustness enhanced sensor assisted monte Carlo localization for wireless sensor networks and the internet of things. IEEE Access 10:33408–33420. https://doi.org/10.1109/ACCESS.2022.3162288

    Article  Google Scholar 

  25. Silmi S, Doukha Z, Moussaoui S (2021) A self-localization range free protocol for wireless sensor networks. Peer-to-Peer Netw Appl 14:2061–2071. https://doi.org/10.1007/s12083-021-01155-w

    Article  Google Scholar 

  26. Manolakis D (1996) efficient solution and performance analysis of 3-D position estimation by trilateration. IEEE Trans Aerosp Electron Syst 32:1239–1248

    Article  ADS  Google Scholar 

  27. Rashid H, Turuk AK (2013) Localization of WSNs using a single anchor node. Wirel Pers Commun 72:975–986. https://doi.org/10.1007/s11277-013-1050-y

    Article  Google Scholar 

  28. SinghWalia G, Singh P, Singh M, Abouhawwash M, JuPark H et al (2022) Three dimensional optimum node localization in dynamic wireless sensor networks. Comput Mater Contin 70(1):305–321. https://doi.org/10.32604/cmc.2022.019171

    Article  Google Scholar 

  29. Johnson DB, Maltz DA (1996) Dynamic source routing in ad hoc wireless networks. Mob Comput 353:153–181

    Article  Google Scholar 

  30. Liang B, Haas ZJ (1999) Predictive distance-based mobility management for PCS networks. IEEE Inf Comm Conf 3:1377–1384

    Google Scholar 

  31. Han G, Jiang J, Duong TQ, Guizani M, Karagiannidis G (2016) A survey on mobile anchor node assisted localization in WSNs. IEEE Commun Surv Tutor. https://doi.org/10.1109/COMST.2016.2544751

    Article  Google Scholar 

  32. Koutsonikolas D, Das SM, Hu YC (2007) Path planning of mobile landmarks for localization in WSNs. Comput Commun 30(13):2577–2593

    Article  Google Scholar 

  33. Huang R, Za ruba GV (2007). Static path planning for mobile beacons to localize sensor networks. In: Fifth Annual IEEE International Conference on Pervasive Computing and Communications Workshops, White Plains, NY, pp 323–330

  34. Hu Z, Gu D, Song Z, Li H (2008) Localization in WSNs using a mobile anchor node. In: IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Xian, pp 602–607

  35. Zhang B, Yu F, Zhang Z (2009) Collaborative localization algorithm for WSNs using mobile anchors. In: 2009 Second Asia-Pacific Conference on Computational Intelligence and Industrial Applications, Wuhan, pp 309–312

  36. Chen H, Liu B, Huang P, Liang J, Gu Y (2012) Mobility-assisted node localization based on TOA measurements without time synchronization in WSNs. Mob Netw Appl 17(1):90–99

    Article  CAS  Google Scholar 

  37. Ssu KF, Ou CH, Jiau HC (2005) Localization with mobile anchor points in WSNs. IEEE Trans Veh Technol 54(3):1187–1197

    Article  Google Scholar 

  38. Ou C, He W (2013) Path planning algorithm for mobile anchor-based localization in WSNs. IEEE Sens J 13(2):466–475

    Article  ADS  Google Scholar 

  39. Khan HM, Olariu S, Eltoweissy M (2006) Efficient single-anchor localization in sensor networks. In: Proceedings of the second IEEE workshop on dependability and security in sensor networks and systems (DSSNS’2006). https://doi.org/10.1109/DSSNS.2006.6

  40. Singh P, Khosla A, Kumar A, Khosla M (2018) Optimized localization of TNs using single mobile AN in WSN. Int J Electron Commun. https://doi.org/10.1016/j.aeue.2018.04.024

    Article  Google Scholar 

  41. Camp T, Boleng J, Davies V (2002) A survey of mobility models for ad hoc network research. Mob Wirel Commun 2(5):483–502

    Article  Google Scholar 

  42. Sabale K, Mini S (2021) Localization in wireless sensor networks with mobile anchor node path planning mechanism. Inf Sci 579:648–666. https://doi.org/10.1016/j.ins.2021.08.004

    Article  MathSciNet  Google Scholar 

  43. Qin Q, Tian Y, Wang X (2021) Three-dimensional UWSN positioning algorithm based on modified RSSI values. Hindawi Mob Inf Syst. https://doi.org/10.1155/2021/5554791

    Article  Google Scholar 

  44. Singh P, Khosla A, Kumar A et al (2018) Computational intelligence based localization of moving target nodes using single anchor node in wireless sensor networks. Telecommun Syst 69:397–411. https://doi.org/10.1007/s11235-018-0444-2

    Article  Google Scholar 

  45. Xu Y, Zhou J, Zhang P (2014) ‘RSS-based source localization when pathloss model parameters are unknown.’ IEEE Commun Lett 18(6):1055–1058. https://doi.org/10.1109/LCOMM.2014.2318031

    Article  Google Scholar 

  46. Thilagavathi P, Manickam JML (2023) Circumcenter based mobile beacon aided localization in wireless sensor networks. In: 2023 3rd International Conference on Pervasive Computing and Social Networking (ICPCSN), Salem, India, pp 1107–1111. https://doi.org/10.1109/ICPCSN58827.2023.00187

  47. Bani Yaseen TM, Awad FH (2022) Intelligent WSN localization using multi-linear regression and a mobile anchor node. In: 2022 13th International Conference on Information and Communication Systems (ICICS), Irbid, Jordan, pp 209–213. https://doi.org/10.1109/ICICS55353.2022.9811188.

  48. Xin J, Xie G, Yan B, Shan M, Li P, Gao K (2022) Multimobile robot cooperative localization using ultrawideband sensor and GPU acceleration. IEEE Trans Autom Sci Eng 19(4):2699–2710. https://doi.org/10.1109/TASE.2021.3117949

    Article  Google Scholar 

  49. Kumar MK, Prasad VK (2021) TASLT: triangular area segmentation based localization technique for wireless sensor networks using AoA and RSSI measures—a new approach. In: 2021 IEEE 18th International Conference on Mobile Ad Hoc and Smart Systems (MASS), Denver, CO, USA, 2021, pp 585–590. https://doi.org/10.1109/MASS52906.2021.00083

  50. Misra S, Kar P, Roy A, Obaidat MS (2014) Existence of dumb nodes in stationary wireless sensor network. J Syst Softw 91:135–146. https://doi.org/10.1016/j.jss.2013.12.039

    Article  Google Scholar 

  51. Kar P, Misra S (2015) Detouring dynamic routing holes in stationary wireless sensor networks in the presence of temporarily misbehaving nodes. Int J Commun Syst 30(4):e3009

    Article  Google Scholar 

  52. Tong F, Ding B, Zhang Y, He S, Peng Y (2022) A single-anchor mobile localization scheme. IEEE Trans Mob Comput. https://doi.org/10.1109/TMC.2022.3221957

    Article  Google Scholar 

  53. Kurt S, Tavli B (2016) Path loss modeling for WSNs: review of models and comparative evaluations. IEEE Antennas Propag Mag. https://doi.org/10.1109/MAP.2016.2630035

    Article  Google Scholar 

  54. Al-Rodhaan M, Alouini M (2013) A comprehensive survey on WSN simulators. J Netw Comput Appl 36(1):1–20

    Google Scholar 

  55. Wang Y, Liang YC (2008) Modeling and simulations of wireless communication systems using MATLAB. Cambridge University Press, Cambridge

    Google Scholar 

  56. Bhat SJ, K. V Santhosh., (2022) A localization and deployment model for WSNs using arithmetic optimization algorithm. Peer-to-Peer Netw Appl 15:1473–1485. https://doi.org/10.1007/s12083-022-01302-x

    Article  Google Scholar 

  57. Paul AK, Sato T (2013) Detour path angular information based range free localization in WSN. J Sens Actuator Netw 2:25–45

    Article  Google Scholar 

  58. Fu Q, Chen W, Liu K, Chen W, Wang X (2010). Study on mobile beacon trajectory for node localization in WSNs. In: IEEE International Conference on Information and Automation, Harbin, pp 1577–1581

  59. Guo Z, Guo Y, Hong F, Jin Z, He Y, Feng Y, Liu Y (2010) Perpendicular intersection: locating wireless sensors with mobile beacon. IEEE Trans Veh Technol 59(7):3501–3509

    Article  Google Scholar 

  60. Han G, Xu H, Jiang J, Shu L, Hara T, Nishio S (2011) Path planning using a mobile AN based on trilateration in WSNs. Wirel Commun Mob Comput 14(14):1324–1336

    Article  Google Scholar 

  61. Kar P, Misra S (2016) Reliable and efficient data acquisition in wireless sensor network in the presence of transfaulty nodes. IEEE Trans Netw Serv Manage 13(1):99–112. https://doi.org/10.1109/TNSM.2016.2516243

    Article  Google Scholar 

  62. Roy A, Misra S, Kar P, Mondal A (2017) Topology control for self-adaptation in wireless sensor networks with temporary connection impairment. ACM Trans Auton Adapt Syst 11(4):1–34. https://doi.org/10.1145/2979680

    Article  Google Scholar 

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Correspondence to Sanjeev Kumar.

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Kumar, S., Singh, M. Auto-localization algorithm for mobile sensor nodes in wireless sensor networks. J Supercomput (2024). https://doi.org/10.1007/s11227-024-05920-5

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