As distributed simulation systems grow in scale and complexity, ensuring real-time data dissemination among heterogeneous subsystems becomes increasingly challenging. This paper proposes a data distribution optimisation framework for simulation agents, combining multi-stage pipeline parallelism and resource reservation for critical task handling. By parallelising data reception, parsing, processing, forwarding, and delivery, the framework reduces latency for time-sensitive tasks. Additionally, resource reservation ensures stable performance under high load by allocating dedicated CPU and memory to critical tasks. Experiments in multi-agent scenarios demonstrate significant reductions in end-to-end latency and improvements in real-time responsiveness. The framework is lightweight, platform-independent, and scalable, offering an effective solution for large-scale distributed simulation.