In this paper3 , we use Bayesian Networks as a means for unsupervised learning and anomaly (event) detection in gas monitoring sensor networks for underground coal mines. We show t...
X. Rosalind Wang, Joseph T. Lizier, Oliver Obst, M...
Abstract. We propose a model for communication in single-hop wireless sensor networks and define and evaluate the performance of a robust, energy balanced protocol for a powerful a...
Traffic patterns in manufacturing machines exhibit strong temporal correlations due to the underlying repetitive nature of their operations. A MAC protocol can potentially learn t...
Clustering and aggregation inherently increase wireless sensor network (WSN) lifetime by collecting information within a cluster at a cluster head, reducing the amount of data thr...
The subject of this article is the long standing open problem of developing a general capacity theory for wireless networks, particularly a theory capable of describing the fundam...
Jeffrey G. Andrews, Nihar Jindal, Martin Haenggi, ...