Recognizing network activity based on hierarchical clustering in optical networks

In this work, we review one of the unsupervised clustering methods to provide low-rank parametric embeddings of network activity patterns. Since optical parameters exhibit spatial and temporal locality, this embedding based on time-series correlation coefficients of optical parameters. To this end, we use hierarchical clustering to create dendrogram representation for different network activity patterns or repeating trends.