Data Stream of Wireless Sensor Networks Based on Deep Learning

Yue-jie Li


The sensor data in wireless sensor networks are continuously arriving in multiple, rapid, time varying, possibly unpredictable, unbounded streams, and no record of historical information is kept. These limitations make conventional Database Management Systems and their evolution unsuitable for streams. Thereby there is a need to build a complete Data Streaming Management System (DSMS), which could process streams and perform dynamic continuous query processing. In this paper, a framework for Adaptive Distributed Data Streaming Management System (ADDSMS) is presented, which operates as streams control interface between arrays of distributed data stream sources and end-user clients who access and analyze these streams. Simulation results show that the proposed method can thus improve overall system performance substantially.


control system, data stream; deep learning; wireless sensor networks

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International Journal of Online and Biomedical Engineering (iJOE) – eISSN: 2626-8493
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