Research on resource scheduling and load balancing algorithm for traffic centralized controller based on command priority

To address the challenge of high-concurrency requests faced by centralized traffic controllers in large-scale urban road networks, this paper proposes a collaborative computing framework that integrates command priority scheduling with load balancing. This framework first constructs a multi-dimensional assessment model for traffic control command priority. It then designs a hierarchical processing mechanism: at the multi-core load balancing layer, a hybrid load balancing strategy is proposed, directing highly critical commands to the least loaded or highest performing processing core, while normal and low commands utilize an improved Weighted Least Connections algorithm for dynamic and balanced allocation of computing resources; at the single-core scheduling layer, a dynamic scheduling algorithm based on strict priority queues is adopted to ensure high-priority commands receive computing resources first. Simulation test results show that compared to traditional scheduling algorithms, the proposed algorithm significantly improves overall system throughput and multi-core processor utilization efficiency while guaranteeing extremely low response latency for high-priority commands, providing core algorithmic support for building high-performance traffic control systems.