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Efficient topology discovery and routing in thick wireless Linear Sensor Networks

机译:厚无线线性传感器网络中的高效拓扑发现和路由

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Wireless devices such as sensors have increasingly more processing, storage, and networking capabilities, making wireless sensor networks (WSNs) get lots of attentions in recent years. In addition, the cost of sensors is constantly decreasing making it possible to use large quantities of these sensors in a wide variety of important applications in environmental, military, commercial, health care, and other fields. In order to monitor certain types of infrastructures, many of these applications involve lining up the sensors in a linear form, making a special class of these networks which are defined as Linear Sensor Networks (LSNs). In this paper, we take advantage of the linearity of the network to design two graph-search-based topology discovery algorithms for LSNs, namely, LNBN and L2BN. LNBN focuses on minimizing the number of messages used to construct the backbone, while L2BN targets to minimizing the average number of communication hops. The proposed algorithms have several good properties. First, they allow for significant improvement in the scalability of the communication process. Second, the linearity of the structure and the discovered backbone can enhance the routing reliability by jumping over failed nodes by increasing the range. Lastly, they do not require sensor nodes to have location detection capabilities such as GPS, which would otherwise lead to higher costs of sensor nodes.
机译:诸如传感器之类的无线设备具有越来越多的处理,存储和联网功能,这使得无线传感器网络(WSN)近年来受到了广泛的关注。另外,传感器的成本不断降低,从而使得有可能在环境,军事,商业,医疗保健和其他领域的各种重要应用中使用大量的这些传感器。为了监视某些类型的基础架构,这些应用中的许多应用都涉及以线性形式排列传感器,从而将这些网络的特殊类别定义为线性传感器网络(LSN)。在本文中,我们利用网络的线性度为LSN设计了两种基于图搜索的拓扑发现算法,即LNBN和L2BN。 LNBN致力于最小化用于构造骨干网的消息数量,而L2BN旨在最小化通信跳数的平均数量。所提出的算法具有几个良好的性质。首先,它们可以显着改善通信过程的可伸缩性。其次,结构的线性和发现的骨干网可以通过增加范围来跳过故障节点,从而提高路由可靠性。最后,它们不需要传感器节点具有诸如GPS之类的位置检测功能,否则将导致传感器节点的成本更高。

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