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Localization-Oriented Network Adjustment in Wireless Ad Hoc and Sensor Networks

机译:无线Ad Hoc和传感器网络中面向本地化的网络调整

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Localization is an enabling technique for many sensor network applications. Real-world deployments demonstrate that, in practice, a network is not always entirely localizable, leaving a certain number of theoretically nonlocalizable nodes. Previous studies mainly focus on how to tune network settings to make a network localizable. However, the existing methods are considered to be coarse-grained, since they equally deal with localizable and nonlocalizable nodes. Ignoring localizability induces unnecessary adjustments and accompanying costs. In this study, we propose a fine-grained approach, localizability-aided localization (LAL), which basically consists of three phases: node localizability testing, structure analysis, and network adjustment. LAL triggers a single round adjustment, after which some popular localization methods can be successfully carried out. Being aware of node localizability, all network adjustments made by LAL are purposefully selected. Experiment and simulation results show that LAL effectively guides the adjustment while makes it efficient in terms of the number of added edges and affected nodes.
机译:本地化是许多传感器网络应用程序的一种启用技术。实际部署表明,在实践中,网络并不总是完全可本地化的,因此会保留一定数量的理论上不可本地化的节点。先前的研究主要集中在如何调整网络设置以使网络可本地化。但是,现有方法被认为是粗粒度的,因为它们同样处理可本地化和不可本地化的节点。忽略本地化会导致不必要的调整和相应的成本。在这项研究中,我们提出了一种细粒度的方法,即本地化辅助定位(LAL),该方法主要包括三个阶段:节点本地化测试,结构分析和网络调整。 LAL触发单轮调整,此后可以成功执行一些流行的定位方法。注意节点可定位性,因此有目的地选择了LAL进行的所有网络调整。实验和仿真结果表明,LAL有效地指导了调整,同时在增加的边数和受影响的节点方面使其有效。

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