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Inference of network state and detection of anomaly network behavior based on the available data play important roles in the big data empowered self-organizing networks for enabling 5G. In this paper, we propose a novel framework of efficient network monitoring and proactive cell anomaly detection based on dimension reduction and fuzzy classification techniques. The enhanced semi-supervised classification...
This invited paper presents some novel ideas on how to enhance the performance of consensus algorithms in distributed wireless sensor networks, when communication costs are considered. Of particular interest are consensus algorithms that exploit the broadcast property of the wireless channel to boost the performance in terms of convergence speeds. To this end, we propose a novel clustering based consensus...
In this paper we propose a gossip algorithm for average consensus in clustered wireless sensor networks called superposition gossiping, where the nodes in each cluster exploit the natural superposition property of wireless multiple-access channels to significantly decrease local averaging times. More precisely, the considered network is organized into single-hop clusters and in each cluster average...
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