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Area coverage estimation model for directional sensor networks

机译:方向传感器网络的区域覆盖估计模型

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>Recently, directional sensor networks (DSNs) have received a great deal of attention owing to their wide range of applications in different fields. A directional sensor has a smaller angle of sensing range compared to an omni-directional sensor. Coverage is one of the fundamental problems of directional sensor networks at present, which reflects how well the environment is monitored. In this paper, we propose a coverage estimation model to estimate coverage problem with boundary effect. In order to guide initial deployment of DSNs and better meet requirements with certain initial coverage probability effectively, a novel probability-based area coverage estimation model with boundary effect, named PCPMB, is proposed. Simulation results show that our proposed model outperforms the previous proposed model without boundary effect.
机译:>最近,由于它们在不同领域的广泛应用程序,定向传感器网络(DSNS)已经引起了大量的关注。 与全向传感器相比,定向传感器具有较小的感测范围。 覆盖范围是目前定向传感器网络的基本问题之一,这反映了对环境的监控程度。 在本文中,我们提出了一个覆盖估计模型来估算边界效应的覆盖问题。 为了指导DSN的初始部署和更好地满足有关某些初始覆盖概率的要求,提出了一种名为PCPMB的边界效果的新型概率的区域覆盖估计模型。 仿真结果表明,我们所提出的模型优于前一个建议的模型而没有边界效果。

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