In order to solve the problems of transmission delay and data loss caused by network congestion and strengthen the quality of service of transmission delay and throughput, a method of flow control in network media information transmission based on differential evolution algorithm was presented. By analyzing the delay effect of buffer on network instability, the problems of flow control at the receiving end were clarified. Moreover, the jitter between packet and end-to-end time delay parameters in dynamic caching mechanism were analyzed. The maximum and minimum values were set to calculate the balance point of real-time communication and smooth network information transmission flow. In addition, the differential evolution algorithm based on adaptive quadratic mutation of population fitness variance was used to improve the adaptive global optimization structure, organize the minimum evolution and input the minimum sample. Through reasonable selection of controller parameters and adaptive calculation, the poles of the closed-loop control system were obtained. Finally, the transmission performance index could be optimized. Thus, the stable control of transmission flow was completed. Simulation results show that the proposed algorithm can effectively improve the transmission performance of heterogeneous networks. Meanwhile, it has obvious advantages when the asymmetric parameters are high.

为了解决网络拥塞引起的传输时延和数据丢失的问题，提高传输时延和吞吐量的服务质量，提出了一种基于差分进化算法的网络媒体信息传输流控制方法。通过分析缓冲区对网络不稳定的延迟影响，明确了接收端流量控制的问题。此外，还分析了动态缓存机制中数据包与端到端时延参数之间的抖动。设置最大值和最小值以计算实时通信的平衡点和平滑的网络信息传输流。此外，采用基于种群适应性方差的自适应二次突变的差分进化算法，改进了自适应全局优化结构，组织了最小进化，并输入了最小样本。通过合理选择控制器参数并进行自适应计算，得出了闭环控制系统的极点。最后，可以优化传输性能指标。这样，完成了传输流量的稳定控制。仿真结果表明，该算法可以有效提高异构网络的传输性能。同时，当不对称参数较高时，具有明显的优势。得到了闭环控制系统的极点。最后，可以优化传输性能指标。这样，完成了传输流量的稳定控制。仿真结果表明，该算法可以有效提高异构网络的传输性能。同时，当不对称参数较高时，具有明显的优势。得到了闭环控制系统的极点。最后，可以优化传输性能指标。这样，完成了传输流量的稳定控制。仿真结果表明，该算法可以有效提高异构网络的传输性能。同时，当不对称参数较高时，具有明显的优势。