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Improved DV-Hop localization algorithm using teaching learning based optimization for wireless sensor networks

Author

Listed:
  • Gaurav Sharma

    (National Institute of Technology)

  • Ashok Kumar

    (National Institute of Technology)

Abstract

Node localization is one of the most critical issues for wireless sensor networks, as many applications depend on the precise location of the sensor nodes. To attain precise location of nodes, an improved distance vector hop (IDV-Hop) algorithm using teaching learning based optimization (TLBO) has been proposed in this paper. In the proposed algorithm, hop sizes of the anchor nodes are modified by adding correction factor. The concept of collinearity is introduced to reduce location errors caused by anchor nodes which are collinear. For better positioning coverage, up-gradation of target nodes to assistant anchor nodes has been used in such a way that those target nodes are upgraded to assistant anchor nodes which have been localized in the first round of localization. For further improvement in localization accuracy, location of target nodes has been formulated as optimization problem and an efficient parameter free optimization technique viz. TLBO has been used. Simulation results show that the proposed algorithm is overall 47, 30 and 22% more accurate than DV-Hop, DV-Hop based on genetic algorithm (GADV-Hop) and IDV-Hop using particle swarm optimization algorithms respectively and achieves high positioning coverage with fast convergence.

Suggested Citation

  • Gaurav Sharma & Ashok Kumar, 2018. "Improved DV-Hop localization algorithm using teaching learning based optimization for wireless sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 67(2), pages 163-178, February.
    • Handle: RePEc:spr:telsys:v:67:y:2018:i:2:d:10.1007_s11235-017-0328-x
    DOI: 10.1007/s11235-017-0328-x
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    References listed on IDEAS

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    1. Mahshid Mehrabi & Hassan Taheri & Pooria Taghdiri, 2017. "An improved DV-Hop localization algorithm based on evolutionary algorithms," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 64(4), pages 639-647, April.
    2. Stefan Tomic & Ivan Mezei, 2016. "Improvements of DV-Hop localization algorithm for wireless sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 61(1), pages 93-106, January.
    3. Shrawan Kumar & D. K. Lobiyal, 2017. "Novel DV-Hop localization algorithm for wireless sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 64(3), pages 509-524, March.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Hend Liouane & Sana Messous & Omar Cheikhrouhou, 2022. "Regularized least square multi-hops localization algorithm based on DV-Hop for wireless sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 80(3), pages 349-358, July.
    2. Soumya J. Bhat & K. V. Santhosh, 2022. "Localization of isotropic and anisotropic wireless sensor networks in 2D and 3D fields," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 79(2), pages 309-321, February.
    3. Tapan Kumar Mohanta & Dushmanta Kumar Das, 2022. "Improved DV-Hop localization algorithm based on social learning class topper optimization for wireless sensor network," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 80(4), pages 529-543, August.
    4. Xiuwu Yu & Yinhao Liu & Yong Liu, 2024. "Optimization of WSN localization algorithm based on improved multi-strategy seagull algorithm," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 86(3), pages 547-558, July.
    5. Haibin Sun & Dong Wang & Hongxing Li & Ziran Meng, 2023. "An improved DV-Hop algorithm based on PSO and Modified DE algorithm," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 82(3), pages 403-418, March.
    6. Hilary I. Okagbue & Muminu O. Adamu & Timothy A. Anake & Ashiribo S. Wusu, 2019. "Nature inspired quantile estimates of the Nakagami distribution," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 72(4), pages 517-541, December.
    7. Shilpi & Arvind Kumar, 2023. "A localization algorithm using reliable anchor pair selection and Jaya algorithm for wireless sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 82(2), pages 277-289, February.

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    2. Mahshid Mehrabi & Hassan Taheri & Pooria Taghdiri, 2017. "An improved DV-Hop localization algorithm based on evolutionary algorithms," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 64(4), pages 639-647, April.
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