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arXiv 1111.4335cs.NI
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无线传感器网络中基于能量感知的节点选择算法

Energy Aware Node Selection for Cluster-based Data Accuracy Estimation in Wireless Sensor Networks

Jyotirmoy Karjee, H. S Jamadagni

摘要:

本文的主要目标是减少传感器节点的数量,通过估计数据的准确性和能量消耗之间的权衡选择节点的概率方法在分布式网络中。设计程序/方法:由于传感器节点的高密度部署,在空间域中的传感器节点之间观察到的数据高度相关。这些传感器节点之间的数据高度相关,形成非重叠的分布式集群。我们为每个分布式集群开发了一个概率模型,以执行网络中的数据准确性和能耗模型。最后,我们找到一个折衷的数据精度和能源消耗模型,以选择一个最佳的传感器节点数量在每个分布式集群。我们还比较了网络中每个分布式集群的数据精度估计模型与信息精度模型的性能。实际应用:物理环境中的温度测量和农业领域中的水分测量。创意/新颖的想法:基于数据准确性和能量消耗权衡的分簇分布式网络中概率方法的最优节点选择。

英文摘要:

The main objective of this paper is to reduce the number of sensor nodes by estimating a trade off between data accuracy and energy consumption for selecting nodes in probabilistic approach in distributed networks. Design Procedure/Approach: Observed data are highly correlated among sensor nodes in the spatial domain due to deployment of high density of sensor nodes. These sensor nodes form non-overlapping distributed clusters due to high data correlation among them. We develop a probabilistic model for each distributed cluster to perform data accuracy and energy consumption model in the network. Finally we find a trade off between data accuracy and energy consumption model to select an optimal number of sensor nodes in each distributed cluster. We also compare the performance for our data accuracy estimation model with information accuracy model for each distributed cluster in the network. Practical Implementation: Measuring temperature in physical environment and measuring moisture content in agricultural field. Inventive /Novel Idea: Optimal node selection in probabilistic approach using the trade of between data accuracy and energy consumption in cluster-based distributed network.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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