Anti-Congestion Algorithm for Multiple Data Unicast Transmission in the Internet of Brain Things

Abstract

Aiming at the problems of traditional cross-talk, channel competition, and data transmission congestion in the brain Internet of Things transmission, a new anti-congestion algorithm for multi-data unicast transmission is proposed. The algorithm calculates the congestion probability of multiple data unicasts by establishing a multi-dimensional conflict model for multiple data transmission channels in the brain Internet of Things. According to the crosstalk characteristic of the network data transmission channel path in the space, the congestion condition of multiple data unicast transmission is detected, and the congestion state of the unicast transmission in the brain Internet of Things is reversed to detect the congestion channel, thereby reducing the congestion-prone data transmission. To achieve anti-congestion transmission, the simulation experiment is carried out on the method. The experimental results show that the method can accurately detect channel path conflict information in multiple data unicast transmissions. It has high-data transmission performance and contributes to the congestion transmission of various data in the brain of the Internet of Things in the future.