WSN中ACSFD分拣网络的VLSI实现

K. Baskaran, M. Raghu, R. R. Kumar
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引用次数: 0

摘要

传统上采用基于协同传感器故障检测(CSFD)的容错分布式决策融合方法。提出了CSFD方案,该方案使用同质性测试的结果来识别网络中的故障节点,从而在估计感兴趣参数时可以过滤掉它们的量化消息。该方案能够有效地识别故障节点,显著提高决策融合的性能。该方法在检测过程中不需要进行指数和乘法/除法等大量的计算,从而获得了很好的性能。在许多实时WSN应用中,融合中心可能在ASIC中实现,并包含在独立设备中。因此,迫切需要一种简单、高效、低硬件成本和低功耗的决策融合方案。在本文中,我们提出了近似协同传感器故障检测(ACSFD)方案及其VLSI架构。为此需要在ACSFD中进行排序操作,找出4个最大故障节点索引供后续使用。我们实现了不同的排序算法来评估排序网络的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
VLSI implementation of sorting network for ACSFD in WSN
A fault-tolerant distributed decision fusion in the presence of sensor faults via Collaborative Sensor Fault Detection (CSFD) was used traditionally. CSFD scheme is proposed in which the results of a homogeneity test are used to identify the faulty nodes within the network such that their quantized messages can be filtered out when estimating the parameter of interest. The scheme can identify the faulty nodes efficiently and improve the performance of the decision fusion significantly. It achieves very good performance at the expense of such extensive computations as exponent and multiplication/division in the detecting process. In many real-time WSN applications, the fusion center might be implemented in an ASIC and included in a stand-alone device. Therefore, a simple and efficient decision fusion scheme requiring lower hardware cost and power consumption is extremely desired. In this paper, we propose the Approximated Collaborative Sensor Fault Detection (ACSFD) scheme and its VLSI architecture. Sorting operation are required in ACSFD to find out four biggest faulty node indexes for subsequent usage for this purpose. we have implemented different sorting algorithm to evaluate the efficiency of the sorting network.
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