Data Clustering in Wireless Sensor Network

Dear Colleagues,

The Internet of Things (IoT) allows for the interconnection of a large number of heterogeneous devices generating a massive amount of data, a relevant part of which is generated by wireless sensor networks. Data clustering is one of the most popular techniques for the analysis of data gathered from sensors. Traditional data-clustering algorithms generally do not satisfy the processing requirements of the IoT, such as energy efficiency and distributed computation. Novel distributed solutions are required, which limit communication costs without compromising model accuracy.

This special issues is addressed to all types of data clustering designed for wireless sensor networks, including but not limited to the topic below:

•     - Distributed hard and soft prototype-based clustering
•     - Distributed gossip-based clustering
•     - Distributed density-based clustering
•     - Distributed micro-cluster based clustering
•     - Distributed optimization-based clustering
•     - Distributed information theoretic clustering
•     - Bio-inspired distributed clustering
•     - Privacy-preserving clustering in sensor networks
•     - Data clustering based on community detection
•     - Stream clustering from wireless sensor network data

Dr. Flavio Zabini
Dr. Stefano Lodi
Guest Editors

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