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A novel approach of localization with single mobile anchor using quantum-based Salp swarm algorithm in wireless sensor networks.

Authors :
Rani, Shalli
Babbar, Himanshi
Kaur, Pardeep
Ali Khan, Asif
Source :
Soft Computing - A Fusion of Foundations, Methodologies & Applications. Sep2023, p1-15.
Publication Year :
2023

Abstract

Quantum software engineering is a field of study that combines principles from quantum computing and classical software engineering. One potential application of quantum software engineering is in the area of wireless sensor networks (WSNs), specifically in the localization of nodes. WSNs are equipped to gather information by detecting the surroundings around smart cities. Numerous applications related to Mobility in Smart Cities (MSC) struggle with routing, security, deployment, extended lifetime, data computation, and localization. Many academics have developed various Computational Intelligence-based techniques for the aforementioned problems to attain high-level performance of MSCs. Quantum software engineering can potentially enhance the accuracy and efficiency of node localization in WSNs. Node localization refers to the process used to locate the target node. Accurately determining the coordinates of static nodes is simple, but locating mobile nodes is more difficult. The performance of the MSC is directly impacted by localization accuracy. In this article, the Quantum-based Salp Swarm Algorithm (QBSSA) is implemented for a range-based and range-free framework. The performance of already existing techniques is evaluated and compared with QBSSA, such as Particle Swarm Optimization (PSO) and H-best Particle Swarm Optimization (HPSO). The mobile anchor node moves in the whole network in a Hilbert path topology and localizes the mobile targets in the network by their random deployment in the area of communication. To minimize the effect of Line of Sight propagation, the Hilbert trajectory is used. The results of the simulation demonstrate that the proposed approach can localize the mobile target with a two-fold reduction in error as opposed to PSO and a 1.5-fold reduction in error as opposed to HPSO, at the same time as the computational time is significantly reduced. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14327643
Database :
Academic Search Index
Journal :
Soft Computing - A Fusion of Foundations, Methodologies & Applications
Publication Type :
Academic Journal
Accession number :
172388769
Full Text :
https://doi.org/10.1007/s00500-023-09261-y