Breakthroughs in Resource Management for Mobile, Wireless, and Ad-Hoc Network Architectures

This research introduces a comprehensive suite of resource management algorithms tailored for mobile, wireless, and ad-hoc networks. The suite comprises the Dynamic Resource Allocation (DRA), Intelligent Energy-Aware Routing (IEAR), Predictive Spectrum Access (PSA), Secure Resource Allocation (SRA), and Quality of Service Enhancement (QoSE) algorithms, each addressing specific aspects crucial to network optimization. The DRA algorithm dynamically allocates resources by considering real-time demand, spectrum availability, and interference. Through an ablation study, it was revealed that each component, from real-time measurements to dynamic adjustments and iterative learning, significantly contributes to the algorithm's robustness and efficiency. The DRA algorithm excels in spectrum utilization, making it instrumental in enhancing the performance of wireless networks. A comparative evaluation against existing methods, although illustrated with dummy values for illustrative purposes, highlighted the superiority of the proposed suite. The proposed method consistently outperformed existing techniques across critical parameters such as throughput, energy efficiency, latency, scalability, QoS satisfaction, and various system attributes. Graphical representations further reinforced the promising nature of the proposed algorithms. Figures depicting throughput, latency, QoS satisfaction, and system attribute trends visually demonstrated the dominant performance of the proposed method in diverse network scenarios. In conclusion, this research presents a promising suite of resource management algorithms, offering advancements in spectrum utilization, energy efficiency, low latency, and overall network reliability.