一种基于灰色模型的预测调度算法

为了保证监控的质量，无线传感器网络通常以高密度的方式部署节点。当这些节点全部处于工作状态时，不仅会引起信道严重的冲突，而且会产生较多的数据，大量消耗节点的能量。因此，让节点轮流工作和休眠，是一种较好的节能方法。论文对此进行了研究，提出了一种基于预测的调度算法。在这个算法中，簇首节点对簇内成员进行管理，并调度低能量的节点进入休眠状态。休眠节点的数据则由簇首节点采用一定的预测算法来预测。仿真结果表明，该调度算法不仅能够有效地延长网络的生命周期，而且数据的精度也能够得到较好的保证。

Prediction Scheduling Algorithm Based on Gray Model

To ensure monitoring quality of wireless sensor networks (WSNs)，sensors were usually deployed densely．If these nodes worked synchronously，they may cause many serious channel conflicts，and generate a quantity of data，which result in a large energy consumption．Hence，it was an energy efficient way to active nodes alternately．It was researched in this paper and a prediction-based scheduling algorithm called PSGM was proposed．In PSGM，cluster heads managed nodes and scheduled the sleeping of nodes with low energy．Then the data of the sleeping nodes would be got by cluster heads with some prediction algorithm．Simulation results showed that PSGM prolonged the lifespan of the network and assured the accuracy of data．