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RNN Based Optimal Sensing Schedule Control for Wireless Sensor Networks

机译:基于RNN的无线传感器网络的最优传感时间表控制

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With the growth of the IoT technologies, the development of WSNs becomes increasingly more important. Since batteries are commonly used as energy sources for sensors in WSNs, high energy efficiency can extend the life of sensors and free them from interference such as energy harvesting. Mobile object tracking is one of the areas where WSNs are used. To save the energy, sensors usually manage multi-mode operation, in which they periodically switch active and inactive modes. There exists a tradeoff between object detection accuracy and energy efficiency. Depending on the object speed, direction and sensor deployment topology, different sensing schedules should be applied. In this paper, we propose a novel RNN-based sensor dynamic duty cycle control method that can determine the optimal sensing schedule of each sensor node. Simulation results show that the proposed model provides accurate object detection performance and achieves high energy efficiency.
机译:随着物联网技术的增长,WSN的发展变得越来越重要。 由于电池通常用作WSNS中传感器的能源,因此高能量效率可以延长传感器的寿命,并使它们免于干扰,例如能量收集。 移动对象跟踪是使用WSN的领域之一。 为了节省能量,传感器通常管理多模式操作,在此期间周期性地切换有效和非活动模式。 物体检测精度与能效之间存在权衡。 根据对象速度,方向和传感器部署拓扑,应应用不同的传感时间表。 在本文中,我们提出了一种基于RNN的传感器动态占空比控制方法,可以确定每个传感器节点的最佳感测时间表。 仿真结果表明,该建议的模型提供了精确的物体检测性能,实现了高能量效率。

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