Distributed Clustering-Based Aggregation Algorithm for Spatial Correlated Sensor Networks
Distributed Clustering-Based Aggregation Algorithm for Spatial Correlated Sensor Networks
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DOI：
10.1109/jsen.2010.2056916
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发表时间：
2011-03-01
影响因子：
4.3
通讯作者：
Ghanem, Moustafa
中科院分区：
文献类型：
--
作者：
Ma, Yajie;Guo, Yike;Ghanem, Moustafa
在无线传感器网络中，已经注意到，监测环境特征的附近传感器节点通常记录类似的值。由于传感器观测值之间的空间相关性，这种数据冗余激发了网络内数据聚合的研究。提出了一种传感器网络的α-局部空间分簇算法。该算法通过测量不同传感器采样数据之间的空间相关性，构造一个支配集作为传感器网络的骨干，并根据支配集的信息描述/汇总性能实现数据聚合。为了评估该算法的性能模式识别的情况下，环境数据。评估表明，我们的算法实现的网络可以提供更高的精度比其他算法的环境信息。
In wireless sensor networks, it is already noted that nearby sensor nodes monitoring an environmental feature typically register similar values. This kind of data redundancy due to the spatial correlation between sensor observations inspires the research of in-network data aggregation. In this paper, an alpha-local spatial clustering algorithm for sensor networks is proposed. By measuring the spatial correlation between data sampled by different sensors, the algorithm constructs a dominating set as the sensor network backbone used to realize the data aggregation based on the information description/summarization performance of the dominators. In order to evaluate the performance of the algorithm a pattern recognition scenario over environmental data is presented. The evaluation shows that the resulting network achieved by our algorithm can provide environmental information at higher accuracy compared to other algorithms.