摘要
研究无线传感网络在数据缺失情况下的准确通信问题。由于传感器节点电源能量有限且不可再生,当节点能量较低时,工作状态不稳定,造成发送数据失败,从而导致数据缺失,传统的通信算法对数据缺失的情况很难有效预测,无法形成有效的补偿性判断,造成通信效果差。提出了一种传感数据融合算法的无线传感网络通信优化方法。运用一种节点自适应方法,获取无线传感网络通信的目标函数,引入节点数据适应度计算方法,为通信服务提供准确的依据。运用蚁群融合算法,在数据缺失的情况下,完成节点差异数据融合过程,弥补缺失造成的误差。实验结果表明,运用改进后的算法能够提高无线传感网络数据缺失情况下通信的准确性,极大的降低了通信的误码率。
In this paper, the accurate communication problem of wireless sensor network in the case of missing data was studied. Since the energy supply of sensor nodes is limited and non - renewable, when the energy of node is low, the working status is unstable, resulting in failure to send data and data loss. It is difficult using traditional communication algorithm to predict the situation of missing data. In this paper, we proposed a communications opti- mization method for wireless sensor network based on sensor data fusion algorithm. Firstly, a node adaptive method was employed to get the objective function of wireless sensor network communication, and introduce the node data fit- ness calculation method, in order to provide an accurate basis for communication services. Then, the use of ant colo- ny algorithm, in the case of missing data, can complete the data fusion of node difference to make up the error caused by data missing. Experimental results show that the use of the algorithm can improve the communication accuracy of wireless sensor network in data loss situations, which greatly reduces the communication error rate.
出处
《计算机仿真》
CSCD
北大核心
2013年第12期249-252,共4页
Computer Simulation
关键词
无线传感网络
数据缺失
通信优化
蚁群算法
Wireless sensor network （WSN）
Data loss
Communication optimization
Ant colony algorithm
