无线传感器网络中一种环状空间相关性模型

Circular spatial correlation model for wireless sensor networks

无线传感器网络特点之一是监测事件的节点分布稠密,相互邻近的节点获得的事件观测值具有很高的相关性。因此,如何消除这种空间相关性以改善网络性能是一个重要的研究课题。提出一种适合无线传感器网络中的事件监测应用的环状空间相关性模型。该模型依据离事件源距离相等节点采样数据空间相关性更高的事实,针对能量衰减模型,采用最小二乘估计对事件源进行更精确的估计。基于新模型,进一步讨论了节点间采样值的空间相关性。模拟实验表明,对传感器网络异常事件监测应用选取适当规模的代表性节点,新模型比现有模型的精确度提高两个数量级以上。新模型能更精确地挖掘传感器网络中的空间相关性,为开发基于空间相关性的传感器网络MAC协议提供了更好的理论框架。

Wireless sensor networks（WSN） are characterized by the dense deployment of sensor nodes that continuously observe physical phenomenon.Due to high density in the network topology,sensor observations was highly correlated in the space domain.It could improve network performance drastically to adopt the spatial correlation.This paper proposed a circular spatial correlation model,which was more suitable for the application of WSN in anomaly detection.According to the fact that the observations of nodes,which had the same distance from an event source,were more correlated,and utilized the least square estimation to estimate the information of the event source based on the energy attenuation model.This paper also discussed the spatial correlation among the observations of nodes based on the new model.Experimental results show that,for the application of anomaly detection in WSN,estimation approach is two orders of magnitude accurate than that of the previous model when the number of representative nodes is larger than some small number.Consequently,the new model is able to exploit the spatial correlation more accurately and provides a better framework for the development of spatial correlation-based medium access control（MAC） protocol in WSN.