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Distributed fault-tolerant classification in wireless sensor networks

机译:无线传感器网络中的分布式容错分类

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摘要

Fault-tolerance and data fusion have been considered as two fundamental functions in wireless sensor networks. In this paper, we propose a novel approach for distributed multiclass classification using a fault-tolerant fusion rule for wireless sensor networks. Binary decisions from local sensors, possibly in the presence of faults, are forwarded to the fusion center that determines the final classification result. Classification fusion in our approach is implemented via error correcting codes to incorporate fault-tolerance capability. This new approach not only provides an improved fault-tolerance capability but also reduces computation time and memory requirements at the fusion center. Code matrix design is essential for the design of such systems. Two efficient code matrix design algorithms are proposed in this paper. The relative merits of both algorithms are also studied. We also develop sufficient conditions for asymptotic detection of the correct hypothesis by the proposed approach. Performance evaluation of the proposed approach in the presence of faults is provided. These results show significant improvement in fault-tolerance capability as compared with conventional parallel fusion networks.
机译:容错和数据融合已被视为无线传感器网络中的两个基本功能。在本文中,我们提出了一种使用容错融合规则的无线传感器网络分布式多类分类的新方法。来自本地传感器的二进制决策(可能存在故障)被转发到融合中心,后者确定最终的分类结果。我们的方法中的分类融合是通过纠错代码实现的,以合并容错功能。这种新方法不仅提供了改进的容错能力,而且减少了融合中心的计算时间和内存需求。代码矩阵设计对于此类系统的设计至关重要。本文提出了两种有效的代码矩阵设计算法。还研究了两种算法的相对优点。我们还为提出的方法开发了渐近检测正确假设的充分条件。提供了在存在故障的情况下所提出的方法的性能评估。这些结果表明,与常规并行融合网络相比,容错能力有了显着提高。

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