An Innovative Priority Queueing Strategy for Mitigating Traffic Congestion in Complex Networks

Optimizing transportation in both natural and engineered systems, particularly within complex network environments, has emerged as a critical area of research. Traditional methods for mitigating congestion have predominantly focused on routing strategies that rely on first-in-first-out (FIFO) queueing disciplines. However, these approaches often overlook the potential of integrating priority queueing strategies into the routing process. This study introduces an innovative generalized priority queueing (GPQ) strategy designed to enhance the performance of existing FIFO-based routing methods. Unlike conventional techniques, the GPQ strategy incorporates a dynamic, priority-based mechanism that aligns with the routing function, enabling adaptive packet prioritization. This approach not only optimizes congestion management but also ensures broad applicability across diverse network architectures. We evaluate the effectiveness of the GPQ strategy through comprehensive simulations on single-layer, two-layer, and dynamic networks. The results show significant improvements in key performance metrics, including network throughput and average packet delay, compared to traditional FIFO-based methods. These findings highlight the versatility and robustness of the GPQ strategy, emphasizing its potential to improve network efficiency across various topologies and configurations. By addressing the limitations of existing methods and proposing a universally applicable solution, this study makes a significant contribution to network optimization, offering a practical and scalable approach to improving transportation efficiency in complex networks.