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A weighted spatial correlation based strategy to improve the event estimation in a Wireless Sensor Networks

机译:基于加权空间相关性的策略,可改善无线传感器网络中的事件估计

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Wireless Sensor Networks (WSN) are characterized of dense deployment of sensor nodes that collectively communicate event information to the sink. Due to high density in the network topology, sensor observations are highly correlated in the space domain. Furthermore, the nature of the physical phenomenon constitutes the temporal correlation between each consecutive observation of a sensor node. These spatial and temporal correlations along with the collaborative nature of the WSN bring significant potential advantages for the development of the efficient communication protocols well-suited for the WSN paradigm. In this paper a multi-zone approach applied to the area monitored by sensor nodes is proposed. It tries to weight the info sensed by sensor on the basis of the distortion area in order to better estimate at sink node the event. A math formulation of the problem and the proposal to weight the space and data info is led out and simulation campaigns in Matlab show the effectiveness of the event estimation.
机译:无线传感器网络(WSN)的特点是密集部署了传感器节点,这些节点共同将事件信息传递到接收器。由于网络拓扑中的高密度,传感器的观测在空间域中高度相关。此外,物理现象的性质构成了传感器节点每次连续观察之间的时间相关性。这些时空相关性以及WSN的协作性质为开发适合于WSN范例的有效通信协议带来了巨大的潜在优势。本文提出了一种应用于传感器节点监测区域的多区域方法。它尝试根据失真区域对传感器感测到的信息进行加权,以便更好地估计接收节点处的事件。提出了问题的数学公式以及权衡空间和数据信息的建议,并且在Matlab中进行的模拟活动显示了事件估计的有效性。

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