Dynamic algorization for selecting tasks in IoTS system
Corressponding author's email:
huanvm@hcmute.edu.vnDOI:
https://doi.org/10.54644/jte.63.2021.60Keywords:
Neural Network, IoTs, Wireless Sensor Network, battery-life, quality of serviceAbstract
Extending the lifespan and improving the quality of information collected by wireless sensor networks using renewable energy is one of the problems of the Internet of Things (IoT) system. To improve the above problem, we propose an algorithm using a Neural network for the purpose of predicting and selecting sensor nodes and can be applied on microcontrollers with low processing and storage capacity. Unlike previous methods that mainly focus on scheduled or deep sleep tasks, the algorithm we recommend makes the sensor node more adaptable to the environment based on the metrics. Real-time at each node. When there is a large data discrepancy, the amount of collected information is increased and when there is no significant change, the sensor node is put into low power duty to ensure battery life. Results from the study show that the algorithm gathers more useful information and battery life is also improved.
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