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Distributed homology algorithm to detect topological events via wireless sensor networks

机译:分布式同源算法通过无线传感器网络检测拓扑事件

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Wireless sensor networks (WSNs) can span large geographical regions and collaboratively monitor environmental phenomena, for example, forest fires. By designing a WSN to detect changes to such phenomena, current environmental monitoring systems could be supplemented, if not replaced. This research focuses on incremental insertion events, arising from the elevation of a single node's sensor reading between two consecutive states of network operation. Homology, a field of topology, is used to detect and differentiate between incremental insertion events of interest. Particular homology tools are translated to a distributed environment for 2-dimensional WSN deployments. The result is a novel distributed algorithm that can compute an incremental insertion event associated with a region comprising n nodes in O(n) time, using O(n) storage, and O(n) data passed via messages. A small-scale, laboratory testbed is developed to evaluate the algorithm. Deployment results indicate that only nodes in physical proximity to an event are tasked, thereby conserving network resources and allowing multiple disparate events to be simultaneously monitored. Further, transmission cost is shown to vary linearly with the size of the evolving region, confirming one component of the formal analysis.
机译:无线传感器网络(WSN)可以跨越较大的地理区域,并可以协同监视环境现象,例如森林大火。通过设计WSN来检测这种现象的变化,可以对当前的环境监控系统进行补充(如果不更换的话)。这项研究的重点是增量插入事件,这是由网络运行的两个连续状态之间的单个节点的传感器读数升高引起的。同源性是一个拓扑领域,用于检测和区分感兴趣的增量插入事件。将特定的同源性工具转换为适用于二维WSN部署的分布式环境。结果是一种新颖的分布式算法,该算法可以使用O(n)存储和通过消息传递的O(n)数据来计算与O(n)时间中包含n个节点的区域相关的增量插入事件。开发了一个小型实验室测试平台来评估算法。部署结果表明,仅对与事件物理邻近的节点执行任务,从而节省了网络资源,并允许同时监视多个不同的事件。此外,传输成本显示出随着演化区域的大小线性变化,这证实了形式分析的一个组成部分。

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