Optimizing Path Costs in Dynamic Network Routing Using a Bio-Inspired 'Sit-and-Wait' Strategy in the Cheetah Chase Algorithm

Routing optimization in dynamic network environments requires innovative strategies to address challenges like
high path costs and inefficient resource utilization. Traditional routing algorithms often rely on static or semidynamic
methods that fail to adapt effectively to changing topologies. To overcome these limitations, this
research introduces a Novel Cheetah Chase Algorithm (CCA) -and-wait" hunting
strategy.
The "sit-and-wait" approach, observed in predator-prey dynamics, involves strategic patience to identify the
most opportune moment for action, minimizing unnecessary energy expenditure while maximizing efficiency.
Translating this strategy into network routing, the CCA incorporates an adaptive decision-making mechanism
that evaluates multiple routing options before selecting the most cost-effective path. By "waiting" for better
opportunities in the network topology and "acting" decisively when the optimal path is identified, the algorithm achieves significant reductions in path costs and enhances overall routing efficiency.