EXPLORING THE IOT HORIZONS: ADAPTIVE THREE-DIMENSIONAL CONFIGURATIONS OF AUTONOMOUS UAVS IN MOBILE SENSOR NETWORKS.

Aiming at the problem of low coverage caused by the difficulty of obtaining the optimal deployment position in existing commonly used distributed deployment algorithms, this paper proposes a three-dimensional (3D) deployment algorithm for Unmanned Aerial Vehicles (UAV) based on potential game. Firstly, a local mutually beneficial game model is designed, and proved the existence of exact potential games and Nash equilibrium in this game model, and the Nash equilibrium solution corresponds to the maximum coverage. Secondly, inspired by the idea of exploration, a solution method based on exploration-based automatic learning machine was designed, and the maximum utility function value of multiple step sizes in the exploration direction is used to update the action selection probability, ensuring the optimal deployment position in each decision cycle. Simulation results show that the proposed distributed deployment algorithm has higher coverage than existing commonly used methods.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-18
DOI
https://doi.org/10.5281/zenodo.14513656
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
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article

EXPLORING THE IOT HORIZONS: ADAPTIVE THREE-DIMENSIONAL CONFIGURATIONS OF AUTONOMOUS UAVS IN MOBILE SENSOR NETWORKS.

Zenodo (CERN European Organization for Nuclear Research)
UAV Applications and Optimization
article

EXPLORING THE IOT HORIZONS: ADAPTIVE THREE-DIMENSIONAL CONFIGURATIONS OF AUTONOMOUS UAVS IN MOBILE SENSOR NETWORKS.

article en

Abstract

Aiming at the problem of low coverage caused by the difficulty of obtaining the optimal deployment position in existing commonly used distributed deployment algorithms, this paper proposes a three-dimensional (3D) deployment algorithm for Unmanned Aerial Vehicles (UAV) based on potential game. Firstly, a local mutually beneficial game model is designed, and proved the existence of exact potential games and Nash equilibrium in this game model, and the Nash equilibrium solution corresponds to the maximum coverage. Secondly, inspired by the idea of exploration, a solution method based on exploration-based automatic learning machine was designed, and the maximum utility function value of multiple step sizes in the exploration direction is used to update the action selection probability, ensuring the optimal deployment position in each decision cycle. Simulation results show that the proposed distributed deployment algorithm has higher coverage than existing commonly used methods.

Zenodo (CERN European Organization for Nuclear Research)
Advanced Materials and Technologies (Slovenia) (SI)
Openalex Percentile: Top 30%
UAV Applications and Optimization
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EXPLORING THE IOT HORIZONS: ADAPTIVE THREE-DIMENSIONAL CONFIGURATIONS OF AUTONOMOUS UAVS IN MOBILE SENSOR NETWORKS. · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS