On Coverage of Wireless Sensor Networks for Rolling Terrains

On Coverage of Wireless Sensor Networks for Rolling Terrains
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滚动地形无线传感器网络覆盖研究

DOI:
10.1109/tpds.2011.69
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发表时间:
2012-01-01
影响因子:
5.3
通讯作者:
Ma, Huadong
Ma, Huadong
中科院分区:
计算机科学2区
文献类型:
--
作者:
Liu, Liang;Ma, Huadong

文献摘要

被引文献

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在无线传感器网络中,如何在随机部署的情况下获得合适的密度以实现区域覆盖是一个非常重要的问题。现有的传感器覆盖研究主要集中在二维平面覆盖上,假设所有传感器都部署在一个理想平面上。相比之下,在许多真实的应用中,传感器也被部署在三维(3D)滚动表面上。为此,我们研究了起伏地形下的无线传感器网络覆盖问题,并推导出随机传感器部署下的期望覆盖率。根据不同的地形特征,本文研究了两类地形覆盖问题:规则地形覆盖问题和不规则地形覆盖问题。具体地说,我们推导了任意曲面z=f(x,y)的期望覆盖率的一般表达式,并建立了两个模型,圆锥模型和余弦旋转模型,用于估计规则地形的期望覆盖率。对于不规则地形,我们提出了一种基于数字高程模型(DEM)的方法来计算预期的覆盖率,并设计了一种算法来估计预期的覆盖率的感兴趣的区域,通过只使用该地区的等高线图。我们还进行了广泛的模拟,以验证和评估我们提出的模型和方案。
Deriving the proper density to achieve the region coverage for random sensors deployment is a fundamentally important problem in the area of wireless sensor networks. Most existing works on sensor coverage mainly concentrate on the two-dimensional (2D) plane coverage which assume that all the sensors are deployed on an ideal plane. In contrast, sensors are also deployed on the three-dimensional (3D) rolling surfaces in many real applications. Toward this end, we study the coverage problem of wireless sensor networks for the rolling terrains, and derive the expected coverage ratios under the stochastic sensors deployment. According to the different terrain features, we investigate two kinds of terrain coverage problems: the regular terrain coverage problem and the irregular terrain coverage problem. Specifically, we derive the general expression of the expected coverage ratio for an arbitrary surface z=f(x, y) and build two models, cone model and Cos-revolution model, to estimate the expected coverage ratios for regular terrains. For irregular terrains, we propose a digital elevation model (DEM) based method to calculate the expected coverage ratio and design an algorithm to estimate the expected coverage ratio of an interested region by using only the contour map of this region. We also conduct extensive simulations to validate and evaluate our proposed models and schemes.