Fox Prey Optimisation: A Novel Multi-Objective Approach for Congestion Control in Wired Computer Networks

The continuous growth in data traffic within wired computer networks demands sophisticated congestion control strategies. This paper introduces an innovative variant of the Fox Prey Optimisation (FPO) algorithm, drawing inspiration from predator-prey dynamics. FPO adeptly adjusts crucial network parameters, skillfully navigating the metaphorical grassland of network challenges. The fox, symbolizing the FPO, strategically pursues optimal solutions scattered across the vast search space. Rigorous simulations consistently demonstrate FPO's efficacy, showcasing notable improvements in latency reduction, packet loss prevention, and throughput enhancement. This contribution not only enriches the optimisation literature but also propels advancements in network efficiency, quality of service, and overall performance. This study offers insights into the dynamic interplay between a predator and its prey within an unpredictable computational landscape. Through FPO, the narrative of innovation in wired computer networks unfolds, emphasizing the value of dynamic pursuit, adaptation, and strategic evolution. The results presented in this paper signify a noteworthy stride towards addressing contemporary challenges in network optimisation.