Optimizing Routing Efficiency in Dynamic Networks Using the Cheetah Chase Algorithm with Novel Convergence Time and Rate Metrics

In dynamic network environments, the efficiency of routing algorithms is often determined by their ability to
converge quickly and stably to the shortest path. Traditional routing algorithms, such as RIP, OSPF, and BGP,
frequently face challenges in achieving consistent convergence, leading to increased latency, routing loops, and
suboptimal performance. To address these issues, this research introduces novel metrics for Convergence
Time and Convergence Rate aimed at achieving minimum path distance while ensuring a stable and reliable
convergence process. The proposed methodology integrates these metrics into the design and evaluation of
routing algorithms, offering a comprehensive approach to performance enhancement. Through simulations and
comparative analysis, the new metrics demonstrate their effectiveness in reducing path costs, improving routing
accuracy, and maintaining stability in both static and dynamic network scenarios.