Flow Control in Network Media Information Transmission Based on Differential Evolution Algorithm

Abstract

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.