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Quality of Information Based Data Selection and Transmission in Wireless Sensor Networks

机译:无线传感器网络中基于信息的数据选择和传输质量

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In this paper, we provide a quality of information (QoI) based data selection and transmission service for classification missions in sensor networks. We first identify the two aspects of QoI, data reliability and data redundancy, and then propose metrics to estimate them. In particular, reliability implies the degree to which a sensor node contributes to the classification mission, and can be estimated through exploring the agreement between this node and the majority of others. On the other hand, redundancy represents the information overlap among different sensor nodes, and can be measured via investigating the similarity of their clustering results. Based on the proposed QoI metrics, we formulate an optimization problem that aims at maximizing the reliability of sensory data while eliminating their redundancies under the constraint of network resources. We decompose this problem into a data selection sub problem and a data transmission sub problem, and develop a distributed algorithm to solve them separately. The advantages of our schemes are demonstrated through the simulations on not only synthetic data but also a set of real audio records.
机译:在本文中,我们为传感器网络中的分类任务提供了基于信息质量(QoI)的数据选择和传输服务。我们首先确定QoI的两个方面,即数据可靠性和数据冗余,然后提出评估它们的指标。特别地,可靠性意味着传感器节点对分类任务的贡献程度,并且可以通过探索该节点与其他大多数节点之间的协议来估计。另一方面,冗余度表示不同传感器节点之间的信息重叠,可以通过调查其聚类结果的相似性来进行度量。基于提出的QoI指标,我们制定了一个优化问题,旨在最大化感官数据的可靠性,同时消除网络资源约束下的冗余。我们将此问题分解为数据选择子问题和数据传输子问题,并开发一种分布式算法分别解决它们。我们的方案的优势不仅通过对合成数据的仿真,而且还对一组真实的音频记录进行了仿真证明。

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