Multi-Objective Dijkstra Algorithm for Enhancing QoS in SDN through Balanced Routing

This study provides a detailed examination of network routing algorithms by comparing the effectiveness of the Time to Live (TTL) algorithm against both Single-objective and Multi-objective Dijkstra algorithms under varying network conditions. The focus of this research centers on assessing and optimizing key network performance indicators including average latency, packet delivery ratio, and bandwidth utilization through the application of different weight configurations within the Multi-objective Dijkstra framework. In conducting a series of comprehensive simulations, the study highlights that the Dijkstra-based algorithms considerably surpass the performance of the TTL algorithm. Notably, the Multi-objective Dijkstra algorithm demonstrates exceptional results, achieving a 100% packet delivery rate across all tested configurations. Furthermore, it manages to strike the most effective balance between latency and bandwidth utilization, confirming the critical role of carefully calibrated algorithm parameters in optimizing network operations. The results distinctly showcase how strategic adjustments to the algorithmic weights can significantly impact the efficiency and effectiveness of network routing, especially in complex and dynamically changing environments. This tailored approach ensures that the algorithms are not only reactive but also proactive in managing network demands efficiently.The paper also discusses potential future research directions that could further refine these findings. One promising area involves the integration of machine learning techniques to facilitate real-time routing decisions, potentially enhancing responsiveness and adaptability in network management. Additionally, applying these advanced routing algorithms to emerging network technologies like 5G and the Internet of Things (IoT) could lead to substantial improvements in data handling and transmission efficiency.