To study the advanced signal processing for big data in industrial production, this study builds an advanced signal processing system for industrial big data. Then, it compares and analyzes the simulation performance of Kafka clusters with MapReduce and Spark algorithms, respectively. The results show that for data transmission, when the successful propagation probability is 100% and the λ value is 0.01–0.05, it is closest to the actual result, and the data propagation delay is gradually smallest. Through a comparative analysis of system performance, it is found that compared to MapReduce and Spark algorithms, Kafka clusters require the shortest running time at the same data scale and the same computing nodes. Further analysis of their packet loss rate indicates that as the number of collection points increases, the amount of transmitted data has only increased slightly, but the packet loss rate has not changed significantly. Therefore, this study suggests that the system can reduce the delay of data transmission and the running time significantly, which provides experimental references for later industrial production and development.


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    Title :

    Advanced Signal Processing for Autonomous Transportation Big Data


    Additional title:

    Internet of Things: Tech., Communicat., Computing


    Contributors:


    Publication date :

    2021-12-15


    Size :

    21 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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