A Sampling-based Boundary Detection Method with Consideration of Boundary Shape in Dense Mobile Wireless Sensor Networks

K. Matsuo, Keisuke Goto, A. Kanzaki, T. Hara
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Abstract

In this paper, we propose a method which efficiently detects the geographical boundaries of sensor readings in mobile wireless sensor networks, in situations where sensor data must be gathered within a short period. Typically, it is enough for detecting the boundaries to gather sensor data only from nodes near the boundaries. However, when the number of such nodes is large, it becomes impossible to gather sensor data from all these nodes within a short period, due to the frequent occurrence of packet collisions. To solve this problem, our proposed method reduces the number of sensor data to be gathered, by taking samples of nodes. When taking samples, our proposed method considers the target boundary shape, in order to suppress the deterioration in the accuracy of the boundaries estimated from the gathered sensor data.
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密集移动无线传感器网络中考虑边界形状的基于采样的边界检测方法
在本文中,我们提出了一种有效检测移动无线传感器网络中传感器读数地理边界的方法,用于必须在短时间内收集传感器数据的情况。通常,仅从边界附近的节点收集传感器数据就足以检测边界。然而,当这类节点数量较大时,由于频繁发生数据包冲突,不可能在短时间内收集到所有这些节点的传感器数据。为了解决这一问题,我们提出的方法通过对节点进行采样来减少需要收集的传感器数据的数量。在采样时,我们提出的方法考虑了目标边界形状,以抑制从采集的传感器数据估计的边界精度的下降。
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