Location Based Distributed Spectral Clustering for Wireless Sensor Networks
Location Based Distributed Spectral Clustering for Wireless Sensor Networks
复制标题
无线传感器网络中基于位置的分布式频谱聚类
DOI：
10.1109/sspd.2017.8233241
复制
发表时间：
2017
期刊：
影响因子：
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通讯作者：
Rafaela Villalpando
中科院分区：
文献类型：
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作者：
Gowtham Muniraju;Sai Zhang;C. Tepedelenlioğlu;Mahesh K. Banavar;A. Spanias;C. Vargas;Rafaela Villalpando
提出了一种分布式谱聚类算法，根据传感器在无线传感器网络 (WSN) 中的位置对传感器进行分组。对于 WSN 中的机器学习和数据挖掘应用，在融合中心收集数据很容易受到攻击并造成数据拥塞。为了避免这种情况，我们提出了一种没有融合中心的鲁棒分布式聚类方法。该算法结合了分布式特征向量计算和分布式K均值聚类。使用分布式幂迭代方法来计算图拉普拉斯的特征向量。在稳定状态下，所有节点收敛到图拉普拉斯代数连通性的特征向量中的值。使用分布式 K 均值算法对特征向量进行聚类。传感器的位置信息仅用于建立网络拓扑，并且该信息不在网络中交换。该算法适用于任何连通图结构。还提供了支持该理论的模拟结果。
A distributed spectral clustering algorithm to group sensors based on their location in a wireless sensor network (WSN) is proposed. For machine learning and data mining applications in WSN's, gathering data at a fusion center is vulnerable to attacks and creates data congestion. To avoid this, we propose a robust distributed clustering method without a fusion center. The algorithm combines distributed eigenvector computation and distributed K-means clustering. A distributed power iteration method is used to compute the eigenvector of the graph Laplacian. At steady state, all nodes converge to a value in the eigenvector of the algebraic connectivity of the graph Laplacian. Clustering is carried out on the eigenvector using a distributed K-means algorithm. Location information of the sensor is only used to establish the network topology and this information is not exchanged in the network. This algorithm works for any connected graph structure. Simulation results supporting the theory are also provided.
DOI：
10.1109/iisa.2017.8316458
发表时间：
2017-08
期刊：
2017 8th International Conference on Information, Intelligence, Systems & Applications (IISA)
影响因子：
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作者：
Sunil Rao;Sameeksha Katoch;P. Turaga;A. Spanias;C. Tepedelenlioğlu;R. Ayyanar;Henry Braun;Jongmin Lee;U. Shanthamallu;M. Banavar;Devarajan Srinivasan
通讯作者：
Sunil Rao;Sameeksha Katoch;P. Turaga;A. Spanias;C. Tepedelenlioğlu;R. Ayyanar;Henry Braun;Jongmin Lee;U. Shanthamallu;M. Banavar;Devarajan Srinivasan
作为物联网 (IoT) 应用的太阳能管理
DOI：
10.1109/iisa.2017.8316460
发表时间：
2017
期刊：
Systems & Applications (IISA
影响因子：
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作者：
Spanias, Andreas S.
通讯作者：
Spanias, Andreas S.