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Aarab, Zineb
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An efficient DVHOP localization algorithm based on simulated annealing for wireless sensor network Arroub, Omar; Darif, Anouar; Saadane, Rachid; Rahmani, My Driss; Aarab, Zineb
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 1: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i1.pp720-736

Abstract

In the last decade, the research community has devoted significant attention to wireless sensor networks (WSNs) because they contribute positively to some critical issues encountered in nature and even in industry. On the other hand, localization is one of the most important parts of WSN. Hence, the conception of an efficient method of localization has become a hot research topic. Lastly, it has been invented, a set of optimal positioning methods that make locate a node with low cost and give precise results. In our contribution, we investigate the source of imprecision in the distance vectorhop (DVHOP) localization algorithm. However, we found the last step of DVHOP caused an imprecision in the calculation. Consequently, our work was to replace this step, aiming to reach satisfactory precision. For that purpose, we created three improved versions of this algorithm by adopting two meta-heuristic (simulated annealing, particle swarm optimization) and Fmincon solver dedicated to optimization in the field of WSN node localization. The experimental results obtained in this work prove the efficiency of simulated annealing (SA)-DVHOP in terms of accuracy. Furthermore, the enhanced algorithm outperforms its opponents by varying the percentage of anchors and the number of nodes.
A new approach for distance vector-Hop localization algorithm improvement in wireless sensor networks Arroub, Omar; Darif, Anouar; Saadane, Rachid; Rahmani, My Driss; Aarab, Zineb
Indonesian Journal of Electrical Engineering and Computer Science Vol 41, No 2: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v41.i2.pp515-531

Abstract

This article shows a new range-free localization technique based on a metaheuristic algorithm (MA) dedicated to wireless sensor network (WSN), named sequential online-grey wolf optimization-distance vector-Hop (SOGWO-DVHOP). Indeed, we use the improved GWO based on selective opposite learning to improve GWO in order to enhance the traditional DVHOP localization algorithm. In reality, we choose GWO due to its better outcomes compared to other meta-heuristics, which leads us to improve this algorithm further. In the literature, the improvement works of GWO try to reconstruct the hierarchy of GWO or improve specifically the role of omega individuals. In our contribution, we opt for opposition-based learning (OBL) to ameliorate GWO, aiming to further enhance the quality of localization made by DVHOP. On the other hand, we make an empirical comparison of DVHOP and its improved versions in terms of accuracy. The results of the simulation demonstrate that SO-GWO-DVHOP gives the best performance when we vary the anchor ratio and the density of nodes.
Co-Authors Anouar Darif Arroub, Omar M. Zairin Junior Rahmani, My Driss