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Distributed Localization Refinements for Mobile Sensor Networks

机译:用于移动传感器网络的分布式定位改进

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Location information is crucial for many applications of sensor networks to fulfill their functions. A mobile sensor network is comprised of both mobile and stationary sensors. So far little work has been done to tackle the mobility of sensors in localization for sensor networks. In this paper, we propose the QoL-guided distributed refinements for anchor-free localization in wireless mobile sensor networks. Accuracy is the core concern for localization. We introduce the important concept of Quality of Localization (QoL) to indicate the accuracy of a computed location for a specific sensor node. Our approach is divided into two phases. In Phase one, we propose the algorithm QoL-guided spreading localization with refinements to compute locations for sensor nodes right after the deployment of the sensor network when the mobile sensors are required to stay static temporarily. In Phase two, the non-movement restriction is released and we propose the mobile location self-updating algorithm to update locations of mobile sensors regularly or on demand. Extensive simulations are conducted, which demonstrate that our approach is a promising technique for localization in wireless mobile sensor networks.
机译:位置信息对于传感器网络的许多应用来满足其功能至关重要。移动传感器网络包括移动和固定传感器。到目前为止,已经完成了很少的工作来解决传感器网络本地化的传感器的移动性。在本文中,我们提出了无线移动传感器网络中无锚定位的QoL引导的分布式改进。准确性是本地化的核心问题。我们介绍了本地化(QOL)质量的重要概念,以指示特定传感器节点的计算位置的准确性。我们的方法分为两个阶段。在第一阶段中,我们提出了算法Qol引导的扩散定位,通过改进来计算传感器网络在移动传感器暂时停留静态之后的传感器网络之后的传感器节点的位置。在第二阶段中,释放非运动限制,我们提出了移动位置自更新算法定期或按需更新移动传感器的位置。进行了广泛的模拟,这表明我们的方法是无线移动传感器网络中定位的有希望的技术。

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