摘要：

网络数据融合与聚类是减少无线传感器网络能量消耗的有效技术,但聚类在数据聚集过程中会产生额外的时间延迟。为此,提出一种基于网络数据融合的延迟感知网络结构,该结构组建传感器节点形成不同大小的簇,每个簇可以与融合中心节点进行交错通信。仿真结果表明,与低功耗自适应集簇分层型协议、延迟感知数据收集网络结构相比,该网络结构可以减少在数据融合过程中的延迟,并能保持较低的能量消耗。

关键词: 数据融合, 聚类, 无线传感器网络, 延迟感知, 融合中心, 能量消耗

Abstract:

Network data fusion and cluster are effective technologies to reduce energy consumption of Wireless Sensor Network(WSN),however,clustering produces extra delays in the process of data aggregation,and the problem can be solved by the modified network structure. A Delay-aware Network Structure for WSNs with Data Fusion(DANSDF)is proposed. The proposed structure organizes sensor nodes into clusters of different sizes,each cluster can communicate with the fusion center in an interleaved manner. Simulation results show that compared with Low Energy Adaptive Clustering Hierarchy(LEACH),Delay-aware Data Collection Network Structure(DADCNS) the two network structures,DANSDF can reduce the delay in the process of data fusion,and can keep a low energy consumption.

Key words: data fusion, clustering, Wireless Sensor Network(WSN), delay-aware, fusion center, energy consumption

中图分类号: 

• TP391