Abstract
Localization systems should be as robust, accurate, and energy-efficient as possible in a wireless sensor network. A centralized localization scheme using a mobile anchor avoids computational overhead at resource-constrained nodes, which improves network lifetime by reducing power consumption. The anchor plays a vital role in accurately estimating the positions of the nodes in the network. Equipping a GPS (Global Positioning System) receiver, an anchor provides reference information to position computation by trilateration or triangulation. Therefore, an anchor coprocessor on dedicated hardware performs the localization faster with low power consumption. In this work, we proposed a localization method in which an anchor centrally computes node positions based on RSS (Received Signal Strength) and AoA (Angle of Arrival) information. We also presented the custom design of anchor coprocessor architecture using the appropriate FSMD (Finite State Machine with Datapath) models and CORDIC (COordinate Rotation DIgital Computer) blocks. The anchor moves along a random path in the network and performs clustering of some neighboring nodes with RSS exceeding a prescribed threshold using a smart antenna. The coprocessor estimates localization information (distance and angle) for the clustering nodes at two distinct anchor points and keeps them in a table. It then computes the positions for nodes encountered twice in the table. Coprocessor performance is tested on a dedicated FPGA (Field Programmable Gate Array) board with multiple fixed-point hardware-level simulations for localization accuracy, computational complexities, and power consumption. The results are comparable to existing systems and corroborate implementation feasibility on wireless network infrastructure with limited resources.
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The datasets generated during the current study are available from the corresponding author on reasonable request.
References
Akyildiz IF, Su W, Sankarasubramaniam Y, Cayirci E (2002) A survey on sensor networks. IEEE Commun Mag 40(8):102–114. https://doi.org/10.1109/MCOM.2002.1024422
Boukerche A, Oliveira HABF, Nakamura EF, Loureiro AAF (2008) Secure localization algorithms for wireless sensor networks. IEEE Commun Mag 46(4):96–101. https://doi.org/10.1109/MCOM.2008.4481347
Biswas RN, Mitra SK, Naskar MK (2019) Preserving security of mobile anchors against physical layer attacks: a resilient scheme for wireless node localization. In: Banday MT (ed) Cryptographic Security solutions for the internet of things. IGI Global, Hershey, pp 250–282
Biswas RN, Mitra SK, Naskar MK (2014) A robust mobile anchor-based localisation technique for wireless sensor network using smart antenna. Int J Ad Hoc Ubiquitous Comput 15(1/2/3):23–37. https://doi.org/10.1504/IJAHUC.2014.059914
Biswas RN, Mitra SK, Naskar MK (2021) Wireless node localization under hostile radio environment using smart antenna. Wirel Pers Commun 116:1815–1836. https://doi.org/10.1007/s11277-020-07763-8
Oliveira LL, Dessbesell GF, Martins JB, Monteiro J (2011) Hardware implementation of a centroid-based localization algorithm for mobile sensor networks. In: Proceedings of the IEEE International Symposium of Circuits and Systems (ISCAS), pp. 2829–2832. Rio de Janeiro, Brazil, 15–18 May 2011. https://doi.org/10.1109/ISCAS.2011.5938194
Zaidi M, Bouazzi I, Al-Rayif MI, Shamim MZM, Usman M (2022) Low power hardware design and its mathematical modeling for fast-exact geolocalization system in wireless networks. Int J Commun Syst 35(9):1–16. https://doi.org/10.1002/dac.5128
Hu X, Wang M, Yan J, Deng J, Dong H (2023) NRAP: nearest reliable anchors-based wireless positioning for irregular multi-hop networks. Wirel Pers Commun 129:2181–2198. https://doi.org/10.1007/s11277-023-10231-8
Liouane H, Messous S, Cheikhrouhou O (2022) Regularized least square multi-hops localization algorithm based on DV-Hop for wireless sensor networks. Telecommun Syst 80:349–358. https://doi.org/10.1007/s11235-022-00897-z
Kanwar V, Kumar A (2021) DV-Hop localization methods for displaced sensor nodes in wireless sensor network using PSO. Wirel Netw 27:91–102. https://doi.org/10.1007/s11276-020-02446-5
Cao Y, Xu J (2023) DV-Hop-based localization algorithm using optimum anchor nodes subsets for wireless sensor network. Ad Hoc Netw 139:1–11. https://doi.org/10.1016/j.adhoc.2022.103035
Mani R, Rios-Navarro A, Sevillano-Ramos J-L, Liouane N (2023) Improved 3D localization algorithm for large scale wireless sensor networks. Wirel Netw. https://doi.org/10.1007/s11276-023-03265-0
Kumar S, Batra N, Kumar S (2023) Optimized localization in large-scale heterogeneous WSN. J Supercomput 79:6705–6729. https://doi.org/10.1007/s11227-022-04922-5
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 78:11975–12023. https://doi.org/10.1007/s11227-022-04320-x
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 35(10):1–15. https://doi.org/10.1002/dac.5147
Bhat SJ, Venkata SK (2020) An optimization based localization with area minimization for heterogeneous wireless sensor networks in anisotropic fields. Comput Netw 179(8):1–10. https://doi.org/10.1016/j.comnet.2020.107371
Cheng M-M, Zhang J, Wang D-G, Tan W, Yang J (2023) A localization algorithm based on improved water flow optimizer and max-similarity path for 3-D heterogeneous wireless sensor networks. IEEE Sens J 23(12):13774–13788. https://doi.org/10.1109/jsen.2023.3271820
Kagi S, Mathapati BS (2022) Localization in wireless sensor network using machine learning optimal trained deep neural network by parametric analysis. Measurement: Sens 24:1–5. https://doi.org/10.1016/j.measen.2022.100427
Liu W, Luo X, Wei G, Liu H (2022) Node localization algorithm for wireless sensor networks based on static anchor node location selection strategy. Comput Commun 192:289–298. https://doi.org/10.1016/j.comcom.2022.06.010
Karalar TC, Yamashita S, Sheets M, Rabaey J (2004) A low power localization architecture and system for wireless sensor networks. In: Proceedings of the IEEE Workshop on Signal Processing Systems (SIPS), pp. 89–94. Austin, TX, USA, 13–15 October. https://doi.org/10.1109/SIPS.2004.1363030
Karalar TC, Yamashita S, Sheets M, Rabaey J (2004) An integrated, low power localization system for sensor networks. In: Proceedings of the IEEE first annual international conference on Mobile and Ubiquitous Systems: Networking and Services (MOBIQUITOUS). pp. 24–30. Boston, MA, USA, 26–26 August. https://doi.org/10.1109/MOBIQ.2004.1331707
Zaidi M, Ouni R, Bhar J, Tourki R (2011) A novel positioning technique with low complexity in wireless LAN: hardware implementation. In: Proceedings of the World Congress on Engineering (WCE). pp. 1806–1812. London, U.K., 6–8 July 2011 ISBN: 978-988-19251-4-5
Liberti JC, Rappaport TS (1999) Smart Antennas for Wireless Communications: IS-95 and third generation CDMA applications. Prentice Hall, New Jersey
Garg VK (2007) Wireless communications and networking. Elsevier Inc, San Francisco
Munoz D, Bouchereau F, Vargas C, Enriquez R (2009) Position location techniques and applications. Elsevier Inc, Burlington
Kurt S, Tavli B (2017) Path-loss modeling for wireless sensor networks: a review of models and comparative evaluations. IEEE Antennas Propag Mag 59(1):18–37. https://doi.org/10.1109/map.2016.2630035
Gross FB (2005) Smart antennas for wireless communications. McGraw-Hill Companies Inc, New York
Civicioglu P (2012) Transforming geocentric cartesian coordinates to geodetic coordinates by using differential search algorithm. Comput Geosci 46:229–247. https://doi.org/10.1016/j.cageo.2011.12.011
Meher PK, Walls J, Juang TB, Sridharan K, Maharatna K (2009) 50 years of CORDIC: algorithms, architectures and applications. IEEE Trans Circuits Syst I Regul Pap 56(9):1893–1907. https://doi.org/10.1109/TCSI.2009.2025803
Chu PP (2008) FPGA Prototyping by Verilog Examples. John Wiley & Sons Inc, New Jersey
Vahid F (2011) Digital Design with RTL Design, VHDL, and Verilog. John Wiley & Sons Inc, New Jersey
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The authors would like to express their gratitude to the esteemed editors and all anonymous reviewers for their valuable suggestions and comments to improve the quality of this paper.
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Rathindra Nath Biswas wrote the main manuscript text including all figures and tables. Anurup Saha and Swarup Kumar Mitra performed experimentation on FPGA to get results. Mrinal Kanti Naskar reviewed the manuscript.
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Biswas, R.N., Saha, A., Mitra, S.K. et al. Design and implementation of anchor coprocessor architecture for wireless node localization applications. Peer-to-Peer Netw. Appl. 17, 961–984 (2024). https://doi.org/10.1007/s12083-024-01640-y
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DOI: https://doi.org/10.1007/s12083-024-01640-y