An innovative approach for cluster head selection and Energy Optimization in wireless sensor networks using Zebra Fish and Sea Horse Optimization techniques

Kingston Roberts, Michaelraj; Ramasamy, Poonkodi; Dahan, Fadl

doi:10.1016/j.jii.2024.100642

Journal of Industrial Information Integration

2024

DOI: 10.1016/j.jii.2024.100642

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An innovative approach for cluster head selection and Energy Optimization in wireless sensor networks using Zebra Fish and Sea Horse Optimization techniques

Michaelraj Kingston Roberts,

Poonkodi Ramasamy,

Fadl Dahan

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Improved DV-Hop algorithm based on geometric Brownian motion model under communication interference

Zhang,

Huang,

Yin

et al. 2024

Meas. Sci. Technol.

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In mobile sensor network, traditional positioning algorithm is unable to locate unknown nodes when losing anchors’ positions caused by communication interference. To solve this problem, an improved DV-Hop algorithm based on Geometric Brownian Motion (GBM) model was proposed including two main stages: location of sink node (LSN) and location of blind node (LBN). In LSN stage, if the signal transmission of anchors is normal, GBM model records the moving positions of anchors. If not, GBM model predicts the estimated average positions of anchors using recorded data. Then, the trial count of GBM model is optimized to further improve the prediction accuracy and computational overhead. In LBN stage, the unknown nodes’ positions are obtained by DV-Hop algorithm. In traditional DV-Hop algorithm, the approximate minimum hop number and average hop distance may lead to huge deviation between true position and estimated position. To improve the positioning accuracy in LBN stage, strategies of multi-communication radius and hop distance weighting were adopted. The simulation results demonstrated that proposed algorithm has the capability of resisting communication interference and adaptability at different speed of nodes, maintaining a relatively high accuracy of locating unknown nodes.

show abstract

Improved DV-Hop algorithm based on geometric Brownian motion model under communication interference

Zhang,

Huang,

Yin

et al. 2024

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

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An innovative approach for cluster head selection and Energy Optimization in wireless sensor networks using Zebra Fish and Sea Horse Optimization techniques

Cited by 1 publication

References 43 publications

Improved DV-Hop algorithm based on geometric Brownian motion model under communication interference

Improved DV-Hop algorithm based on geometric Brownian motion model under communication interference

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