Distributed Clustering Strategies in Industrial Wireless Sensor Networks

作     者：Cenedese, Angelo Luvisotto, Michele Michieletto, Giulia 

作者机构：Univ Padua Dept Informat Engn I-35131 Padua Italy ABB Corp Res Ctr Vasteras Sweden CNRS LAAS Toulouse France 

出 版 物：《IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS》 (IEEE Trans. Ind. Inf.)

年 卷 期：2017年第13卷第1期

页      面：228-237页

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 0808[工学-电气工程] 08[工学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Italian MIUR Project SEAL-Smart&safe Energy-Aware Assisted Living [SCN-00398] 

主　　题：Anomaly detection distributed algorithms environment monitoring industrial wireless sensor networks (IWSNs) network clustering 

摘      要：Wireless sensor networks (WSNs) can provide numerous benefits in industrial automation. By removing the cable infrastructure, the wireless architecture enables the possibility for nodes in a network to dynamically and autonomously group into clusters according to the communication features and the data they collect. This capability allows to leverage the flexibility and robustness of industrial WSNs in supervisory intelligent systems for high-level tasks, such as, for example, environmental sensing, condition monitoring, and process automation. In this paper, a clustering strategy is studied that partitions a sensor network into a nonfixed number of nonoverlapping clusters according to the communication network topology and measurements distribution: To this aim, both a centralized and a distributed algorithm are designed that do not require a cluster-head structure or other network assumptions. As a validation, these strategies are tested on a real dataset coming from a structured environment and the effectiveness of the clustering procedure is also investigated to perform anomalies detection in an industrial production process.