Design of Parallel Big Data Stream Transmission System Based on Chaotic Migration Learning

Aiming at the problems of severe node congestion, low data transmission rate, and low data integrity in the current parallel data transmission process, a method for controlling the integrity of parallel data transmission in a big data environment is proposed; the integrity control principle of parallel data transmission is used to control the parallel data during transmission. Obtain and measure the two major interference factors of transmission congestion for analysis. In order to solve this problem, a parallelized big data streaming system based on migration learning is proposed. This paper studies the design of a parallel big data stream transmission system based on chaotic migration learning.