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Two novel subjective logic-based in-network data processing schemes in wireless sensor networks

机译:无线传感器网络中两种新颖的基于主观逻辑的网络内数据处理方案

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Wireless sensor networks (WSNs) consist of connected low-cost and small-size sensor nodes. The sensor nodes are characterized by various limitations, such as energy availability, processing power, and storage capacity. Typically, nodes collect data from an environment and transmit the raw or processed data to a sink. However, the collected data contains often redundant information. An in-network processing scheme attempts to eliminate or reduce such redundancy in sensed data. In this paper, we propose two in-network data processing schemes for WSNs, which are built based on a lightweight algebra for data processing. The schemes bring also benefits like decreased network traffic load and increased reliability for a network. For trust generation, we employ subjective logic based calculations to mitigate trust fluctuations caused by internal and external factors. Numerical results based on synthetic data reveal the effectiveness and preciseness of our proposed schemes.
机译:无线传感器网络(WSN)由连接的低成本和小型传感器节点组成。传感器节点的特征在于各种限制,例如能量可用性,处理能力和存储容量。通常,节点从环境中收集数据,并将原始或已处理的数据传输到接收器。但是,收集的数据通常包含冗余信息。网络内处理方案试图消除或减少感测数据中的这种冗余。在本文中,我们提出了两种针对WSN的网络内数据处理方案,它们是基于轻量级代数构建的,用于数据处理。该方案还带来了一些好处,例如减少了网络流量负载并提高了网络的可靠性。对于信任的产生,我们采用基于主观逻辑的计算来减轻由内部和外部因素引起的信任波动。基于综合数据的数值结果显示了我们提出的方案的有效性和准确性。

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