A Novel OSPF Routing Optimization Framework for Enhancing Network Performance in Dynamic Network Environment

Abstract

Open Shortest Path First (OSPF) is one of the most widely adopted link-state routing protocols in modern IP networks due to its scalability, reliability, and rapid route computation capabilities. However, in dynamic network environments characterized by frequent topology changes, varying traffic loads, and link failures, conventional OSPF routing often experiences increased convergence delays, network congestion, and suboptimal path selection. This study proposes a novel OSPF routing optimization framework designed to enhance network performance through dynamic route cost adaptation based on multiple network parameters, including bandwidth utilization, end-to-end delay, packet loss, and link congestion levels. The proposed framework employs a modified cost computation mechanism that continuously evaluates network conditions and updates routing decisions to achieve efficient traffic distribution and improved resource utilization. The performance of the proposed model is evaluated using MATLAB-based network simulations under various traffic scenarios and topology conditions. Key performance metrics, including throughput, packet delivery ratio, average delay, packet loss rate, and convergence time, are analyzed and compared with those of the conventional OSPF protocol. Simulation results demonstrate that the proposed framework significantly improves network throughput, reduces routing overhead, minimizes packet loss, and accelerates convergence in dynamic environments. The findings suggest that the optimized OSPF framework provides a scalable and adaptive routing solution suitable for enterprise networks, Internet Service Providers (ISPs), and next-generation communication infrastructures.