基于指数平均模型的无线传感器网络动态功耗管理

Dynamic Power Management Based on Exponential Average Model for WSN

能耗一直是制约无线传感器网络WSN(Wireless Sensor Networks)发展的关键因素。为了降低节点的功耗,延长WSN的寿命,一种改进指数平均模型的动态功耗管理DPM(Dynamic Power Management)方法被提出。该方法利用历史空闲时间来对未来空闲时间进行预测,预测结果作为节点是否转换为低功耗状态的依据。理论分析和实验仿真表明,本文提出的DPM在突发情况时能够快速自适应地调整,提高了预测的准确性,降低了WSN的功耗。

The key factor hindering the development of Wireless sensor network（ WSN） is the energy. In order to re-duce the power consumption and extend the node life time of WSN,an effective method of dynamic power manage-ment strategy based on exponential average model is proposed in this paper. The strategy uses historical idle time to make predictions about the future idle time,and the prediction result will be the basis to decide whether the node is converted into a low power state or not. Facing the burst situations, theoretical analysis and experimental results show that the proposed algorithm can adjust quickly adaptive to improve the accuracy of forecasts and reduce the power consumption of the system.