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Intensive research has focused on redundance reduction in wireless sensor networks among sensory data due to the spatial and temporal correlation embedded therein. In this paper, we propose a novel approach termed asynchronous sampling that complements existing study. The key idea of asynchronous sampling is to spread the sampling times of the sensor nodes(More)
Identifying locations of nodes in wireless sensor networks (WSNs) is critical to both network operations and most application level tasks. Sensor nodes equipped with geographical positioning system (GPS) devices are aware of their locations at a precision level of few meters. However, installing GPS devices on a large number of sensor nodes is not only(More)
In this paper, asynchronous sampling is proposed as a novel approach to improve the information quality of sensory data through shifting the sampling moments of sensors from each other. The exponential correlation model and the entropy model for the sensory data are introduced to quantify their information quality. An asynchronous sampling strategy, EASS,(More)
In this paper, the authors explore a novel method based on asynchronous sampling in order to reduce the data redundancy among spatially correlated nodes in wireless sensor networks. The authors show that when the sensor nodes sample the interested field at different time points, the correlation among the sensory data can be effectively reduced and hence the(More)
Among developing industrialized countries, under the trend of industrial globalization, multinational enterprises give more attention to the quality issue of the products. Response optimization is the goal of much design of experiment which is one of the most important tools in modern quality engineering. Desirability function approach is the most popular(More)
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