Elimination algorithm of complex network redundant data stream based on information theory

Abstract

Aiming at the problem that the traditional method eliminates the bad effect and low accuracy in the process of eliminating redundant data flow in complex networks, an information network-based redundant network redundant data flow elimination algorithm is proposed.Entropy theory is used to optimize the control of complex network data streams, and noise reduction processing is implemented to preprocess the complex network data stream, use information entropy to eliminate red light in complex networks, and eliminate complex network redundant data through information elimination algorithm. The internal data set of the stream. The effective elimination of redundant data streams of complex networks is realized.The experimental results show that the average running time of using the algorithm to eliminate redundant data streams in the college campus network is 0.6004ms, the correct rate is as high as 93.704 \begin{document}$ \% $\end{document} , and the maximum energy consumption is only 398J.It eliminates more redundant data streams, that is to say, the algorithm can eliminate complex network redundant data streams with high efficiency, low energy consumption and precision.