research-article

Hop-Count Quantization Ranging and Hybrid Cuckoo Search Optimized for DV-HOP in WSNs

Authors:

Mufang HuAuthors Info & Claims

Volume 108, Issue 4

Pages 2031 - 2046

https://doi.org/10.1007/s11277-019-06507-7

Published: 01 October 2019 Publication History

Abstract

Localization technology occupies a very important position in wireless sensor network (WSN). Distance vector-hop (DV-HOP) algorithm is range-free localization algorithm and has advantages of low overhead and can handle the case where a normal node has less than three neighbor anchors. However, considering the problem of high localization error of DV-HOP algorithm in WSN. An hybrid DV-HOP localization algorithm based on hop-count quantization anchor and modified cuckoo search (HMCS-D) is proposed. The algorithm using the correction factor to correct the number of hops that can reduce the error caused by the recording inaccurate minimum hops. The nodes of the hop neighbor nodes in the network are divided into three disjoint subsets and the distance between the nodes is estimated according geometric method. Then according to the weight of each anchor node to select average jump distance of unknown nodes. Finally, introduced hybrid cuckoo search which can dynamically adjust the search step size and using the search algorithm to calculate the node coordinates instead of the maximum likelihood estimation method. Simulation results show that compare with DV-HOP and cuckoo search DV-HOP algorithm, the average positioning error of HMCS-D algorithm decrease 39.7%, 10.6% respectively. Prove that the HMCS-D algorithm effectively improve the node localization accuracy, reduce the positioning error and without affecting the hardware cost.

References

[1]

Huang, B., Yu, C., & Anderson, B. D. O. (2013). Understanding error propagation in multihop sensor network localization. IEEE Transactions on Industrial Electronics, 60(12), 5811–5819.

[2]

Gui, L., Val, T., & Wei, A. (2015). Improvement of range-free localization technology by a novel DV-HOP protocol in wireless sensor networks. Ad Hoc Networks, 24(PB), 55–73.

[3]

Zivkovic, M., Nikolic, B., Protic, J., & Popovic, R. (2014). A survey and classification of wireless sensor networks simulators based on the domain of use. Ad Hoc & Sensor Wireless Networks, 20(3–4), 245–287.

[4]

Wu, Y., Li, L., Ren, Y., Yi, K., & Yu, N. (2014). A rssi localization algorithm and implementation for indoor wireless sensor networks. Ad Hoc & Sensor Wireless Networks, 22(3), 309–337.

[5]

Golestanian, M., & Poellabauer, C. (2016). Localization in heterogeneous wireless sensor networks using elliptical range estimation. In International conference on computing, networking and communications (pp. 1–7). IEEE.

[6]

Mass-Sanchez, J., Ruiz-Ibarra, E., Cortez-González, J., Espinoza-Ruiz, A., & Castro, L. A. (2016). Weighted hyperbolic DV-HOP positioning node localization algorithm in WSNS. Wireless Personal Communications, 96, 1–23.

[7]

Farmani, M., Moradi, H., & Asadpour, M. (2012). A hybrid localization approach in wireless sensor networks using a mobile beacon and inter-node communication. In IEEE international conference on cyber technology in automation, control, and intelligent systems (pp. 269–274). IEEE.

[8]

Henriques, V., & Malekian, R. (2016). Mine safety system using wireless sensor network. IEEE Access, 4, 3511–3521.

[9]

Han, S., Gong, Z., Meng, W., Li, C., Zhang, D., & Tang, W. (2016). Automatic precision control positioning for wireless sensor network. IEEE Sensors Journal, 16(7), 2140–2150.

[10]

Li, Y. (2014). An improved DV-HOP localization algorithm based on energy-saving non-ranging optimization. Journal of Networks, 9(11), 3182–3188.

[11]

Gui, L., Zhang, X., Ding, Q., Shu, F., & Wei, A. (2017). Reference anchor selection and global optimized solution for DV-HOP localization in wireless sensor networks. Wireless Personal Communications, 96(1), 1–11.

[12]

Meng, W., Zhao, J., & Ma, S. (2016). High precision multi-communication radius DV-HOP localization algorithm. Communications Technology, 49(06), 701–710.

[13]

Cheng, C., Qian, Z., Fu, C., et al. (2015). Genetic optimization DV-HOP localization algorithm based on error distance weighted and hop algorithm selection. Journal of Electronics&Information Technology, 37(10), 2418–2423.

[14]

Wu, Y., & Li, J. W. (2012). Improved DV-HOP localization algorithm based on optimal communication radius of nodes. Journal of South China University of Technology (Natural Science Edition), 40(06), 36–42.

[15]

Liu, D. F., Zhang, L., Bing, X. Y., Shao, Y. Q., & Xu, B. G. (2017). Localization method based on modified cuckoo difference optimization for wireless sensor networks. Journal of System Simulation, 29(04), 791–797.

[16]

Aziz, M. A. E. (2015). Source localization using TDOA and FDOA measurements based on modified cuckoo search algorithm. Wireless Networks, 23(2), 1–9.

[17]

Xue, Y. G., & Deng, H. W. (2014). The cuckoo search algorithm based on dynamic grouping to adjust flight scale. Applied Mechanics and Materials, 543–547, 1822–1826.

[18]

Salimi, H., Giveki, D., Soltanshahi, M. A., & Hatami, J. (2012). Extended mixture of MLP experts by hybrid of conjugate gradient method and modified cuckoo search. International Journal of Artificial Intelligence & Applications, 3(1), 1–13.

[19]

Zheng, H., & Zhou, Y. (2012). A novel cuckoo search optimization algorithm base on gauss distribution. Journal of Computational Information Systems, 8(10), 4193–4200.

[20]

Song, G., & Tam, D. (2015). Two novel DV-HOP localization algorithms for randomly deployed wireless sensor networks. Abingdon: Taylor & Francis Inc.

[21]

Guo, Z., Min, L., Li, H., & Wu, W. (2012). Improved DV-HOP Localization algorithm based on RSSI value and hop correction. Berlin: Springer.

[22]

Sangwoo, L., Dongyul, L., & Chaewoo, L. (2011). Enhanced DV-HOP algorithm with reduced hop-size error in ad hoc networks. IEICE Transactions on Communications, 94-B(7), 2130–2132.

[23]

Pandey, S., & Varma, S. (2016). A range based localization system in multihop wireless sensor networks: A distributed cooperative approach. Wireless Personal Communications, 86(2), 615–634.

Digital Library

[24]

Shahzad, F., Shaltami, T., & Shakshukhi, E. (2017). DV-maxHop: A fast and accurate range-free localization algorithm for anisotropic wireless networks. IEEE Transactions on Mobile Computing, 16(9), 2494–2505.

Digital Library

[25]

Hu, Y., & Li, X. (2013). An improvement of DV-HOP localization algorithm for wireless sensor networks. Telecommunication Systems, 53(1), 13–18.

Digital Library

[26]

Chao, J., Han, G., Zhu, C., Guo, H., & Shu, L. (2013). Performance evaluation of DV-HOP localization algorithm with mobility models for mobile wireless sensor networks. In Wireless communications and mobile computing conference (vol. 8711, pp. 1827–1832). IEEE.

[27]

Cui, Z., Sun, B., Wang, G., Xue, Y., & Chen, J. (2016). A novel oriented cuckoo search algorithm to improve DV-HOP performance for cyber–physical systems. Journal of Parallel & Distributed Computing, 103, 42–52.

Digital Library

[28]

Chen, Z., Li, X., Yang, B., & Zhang, Q. (2015). A self-adaptive wireless sensor network coverage method for intrusion tolerance based on trust value. Journal of Sensors, 2015(4), 1–10.

Digital Library

[29]

Cheng, J., & Xia, L. (2016). An effective cuckoo search algorithm for node localization in wireless sensor network. Sensors, 16(9), 1390.

[30]

Li, X., & Yin, M. (2015). Modified cuckoo search algorithm with self adaptive parameter method. Information Sciences, 298(C), 80–97.

[31]

Walton, S., Hassan, O., Morgan, K., & Brown, M. R. (2011). Modified cuckoo search: A new gradient free optimisation algorithm. Chaos, Solitons & Fractals, 44(9), 710–718.

[32]

Piechocki, J., Ambroziak, D., Palkowski, A., & Redlarski, G. (2014). Use of modified cuckoo search algorithm in the design process of integrated power systems for modern and energy self-sufficient farms. Applied Energy, 114(114), 901–908.

Cited By

Cui HWang SZhou C(2023)A high-accuracy and low-energy range-free localization algorithm for wireless sensor networksEURASIP Journal on Wireless Communications and Networking10.1186/s13638-023-02246-32023:1Online publication date: 2-May-2023
https://dl.acm.org/doi/10.1186/s13638-023-02246-3
Niranjan MGupta SSingh B(2023)Sensor node localization with improved hop-size using PSODESA optimizationWireless Networks10.1007/s11276-023-03242-729:4(1911-1934)Online publication date: 1-May-2023
https://dl.acm.org/doi/10.1007/s11276-023-03242-7
Yu XHuang LLiu YZhang KLi PLi Y(2022)WSN node location based on beetle antennae search to improve the gray wolf algorithmWireless Networks10.1007/s11276-021-02875-w28:2(539-549)Online publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1007/s11276-021-02875-w
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Hop-Count Quantization Ranging and Hybrid Cuckoo Search Optimized for DV-HOP in WSNs

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Information & Contributors

Information

Published In

cover image Wireless Personal Communications: An International Journal

Wireless Personal Communications: An International Journal Volume 108, Issue 4

Oct 2019

637 pages

ISSN:0929-6212

Issue’s Table of Contents

Copyright © 2019 Springer Science+Business Media, LLC, part of Springer Nature.

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 October 2019

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Cited By

Cui HWang SZhou C(2023)A high-accuracy and low-energy range-free localization algorithm for wireless sensor networksEURASIP Journal on Wireless Communications and Networking10.1186/s13638-023-02246-32023:1Online publication date: 2-May-2023
https://dl.acm.org/doi/10.1186/s13638-023-02246-3
Niranjan MGupta SSingh B(2023)Sensor node localization with improved hop-size using PSODESA optimizationWireless Networks10.1007/s11276-023-03242-729:4(1911-1934)Online publication date: 1-May-2023
https://dl.acm.org/doi/10.1007/s11276-023-03242-7
Yu XHuang LLiu YZhang KLi PLi Y(2022)WSN node location based on beetle antennae search to improve the gray wolf algorithmWireless Networks10.1007/s11276-021-02875-w28:2(539-549)Online publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1007/s11276-021-02875-w
Huang XHan DWeng TWu ZHan BWang JCui MLi K(2022)A localization algorithm for DV-Hop wireless sensor networks based on manhattan distanceTelecommunications Systems10.1007/s11235-022-00943-w81:2(207-224)Online publication date: 1-Oct-2022
https://dl.acm.org/doi/10.1007/s11235-022-00943-w
Li XWang KLiu BXiao JHan S(2020)An improved range-free location algorithm for industrial wireless sensor networksEURASIP Journal on Wireless Communications and Networking10.1186/s13638-020-01698-12020:1Online publication date: 22-Apr-2020
https://dl.acm.org/doi/10.1186/s13638-020-01698-1
Qin XXia BDing TZhao L(2020)An improved Cuckoo search localization algorithm for UWB sensor networksWireless Networks10.1007/s11276-020-02465-227:1(527-535)Online publication date: 25-Sep-2020
https://dl.acm.org/doi/10.1007/s11276-020-02465-2

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