基于分簇无线传感网的高能效数据融合算法

Energy efficient data fusion algorithm base on clustered wireless sensor networks

无线传感器网络通常能量有限且容易受到环境干扰,为了提高无线传感器网络的能效并保障数据的可靠性,提出一种基于分簇无线传感网的高能效数据融合算法(EEDFA).EEDFA在分簇结构的网络中运行,数据的采集与传输过程分为多个周期,传感器在周期内的多个时隙采集数据形成数据向量.每个周期传感器将采集到的数据向量进行降维以降低传输负载,同时考虑环境干扰利用区间二型模糊系统生成数据可靠性因子以保障数据的可靠性.各簇头接收来自成员节点的数据进行分布式处理,利用相似度函数去除冗余数据,将融合后的数据发送至下一跳簇头或基站.仿真结果表明,与PFF、REDA、SCDRE相比,EEDFA具有较低的带宽占用率和能耗,同时具有较高的数据准确率.

The energy of wireless sensor network is limited and the network is vulnerable to the environment.To improve the energy efficiency and data reliability of wireless sensor networks,an energy efficient data fusion algorithm based on clustered wireless sensor networks(EEDFA)is proposed.EEDFA runs in the clustered network,in which the process of data collection and transmission is divided into several periods.Sensors collect data in time slots of the period and form a data vector whose dimension will be reduced to reduce the transmission load.At the same time,the interval type-2 fuzzy system is used to generate data reliability factors considering environmental interference to ensure the reliability of data.Each cluster head receives and distributed processing the data from their member nodes.After removing redundant data by the similarity function,the fused data is sent to the next hop cluster head or base station.Simulation results verify that EEDFA has lower bandwidth occupancy,lower energy consumption,and higher data accuracy than PFF,REDA,and SCDRE.