Optimizing Energy Efficiency in UAV-Based Wireless Communication Networks: A Comparative Analysis of TAODV and DSR Protocols using the Trust Score Algorithm for Signal Processing

Abstract

This study presents a comprehensive analysis of energy efficiency optimization in signal processing algorithms for UAV-based wireless communication networks. Employing a multifaceted approach that integrates mathematical modeling, game theory analysis, and an array of testing methodologies, the research aims to address the critical challenge of enhancing communication protocol performance while minimizing energy consumption. Central to our investigation is the development and application of the Trust Score Algorithm (TSA), a novel quantitative tool designed to evaluate and compare the efficacy of various signal processing algorithms across multiple dimensions, including energy efficiency, reliability, adaptability, security, and latency. Through detailed comparative analysis and data visualization techniques, the study reveals that the Proposed_TAODV protocol significantly outperforms traditional TAODV and DSR protocols in several key metrics. These include throughput efficiency, end-to-end delay, and packet delivery ratio, particularly as the number of UAV nodes scales up. Such findings underscore the Proposed_TAODV protocol's superior stability and performance, advocating for its potential in improving the sustainability and effectiveness of UAV-based communication networks. The research methodology encompasses both theoretical and empirical testing phases, ranging from simulation-based analysis, to validate the performance of the signal processing algorithms under varied operational conditions. The results not only affirm the superior performance of the Proposed_TAODV protocol but also highlight the utility of the TSA in guiding the selection and optimization of signal processing algorithms for UAV networks.