基于二次灰色马尔科夫预测的WSN状态判定算法

State determination algorithm of WSN based on twice grey Markov forecasting

为了节约无线传感器网络中节点的能源,对灰色预测模型进行改进,提出二次无偏灰色马尔科夫预测模型。该模型借鉴马尔科夫预测思想,根据状态判定准则及二次无偏灰色预测,对无线传感器网络的环境状态进行判定,并传输状态标识,从而降低网络节点的能量消耗。仿真结果表明,该模型不仅提高了预测精度,而且获得了有效的状态预测结果。

According to characteristics of wireless sensor networks, for the sake of saving energy of nodes in wireless sensor networks, a twice-unbiased Grey-Markov forecasting model is proposed. Based on Markov prediction, according to the state determination rule and twice-unbiased Gray prediction, the environment state of wireless sensor networks is determined, and the flag of the state is transferred, so that wireless sensor networks can reduce the energy consumption. Simulation results show that the model improves the prediction accuracy and achieves effective state prediction.