Abstract
This paper describes novel approaches for assessing the quality of mote partitioning in Wireless Sensor and Actuators Networks (WSANs) that allows optimization of the topology of WSANs. The proposed solution aims to supports node placement and activation strategies both at the time of sensor deployment and during the network normal operation. A blend of statistical and unsupervised learning techniques is proposed to test the quality of the WSAN organisation. A formal review and interpretation of various metrics is provided. These metrics can be used to improve management of resources in WSAN infrastructures. © 2013 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Chaczko, Z., & Resconi, G. (2013). Assessing the quality of WSAN topologies. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8112 LNCS, pp. 174–182). Springer Verlag. https://doi.org/10.1007/978-3-642-53862-9_23
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