Aug 20, 2012 · This paper deals with a crucial network monitoring task termed dynamic anomalography. Given link traffic measurements (noisy superpositions of unobserved OD ...

After recasting the non-sepa- rable nuclear norm into a form amenable to online optimization, a real-time algorithm for dynamic anomalography is developed and.

Dec 5, 2024 · This paper deals with a crucial network monitoring task termed dynamic anomalography. Given link traffic measurements (noisy superpositions of unobserved OD ...

Comprehensive numerical tests with both synthetic and real network data corroborate the effectiveness of the proposed online algorithms and their tracking ...

In the backbone of large-scale networks, origin-to-destination (OD) traffic flows experience abrupt unusual changes known as traffic volume anomalies, ...

Dive into the research topics of 'Dynamic anomalography: Tracking network anomalies via sparsity and low rank'. Together they form a unique fingerprint. Sort by ...

Dive into the research topics of 'Dynamic anomalography: Tracking network anomalies via sparsity and low rank'. Together they form a unique fingerprint. Sort by ...

2009. Dynamic anomalography: Tracking network anomalies via sparsity and low rank. M Mardani, G Mateos, GB Giannakis. Selected Topics in Signal Processing ...

Dynamic Anomalography: Tracking Network Anomalies via Sparsity and Low Rank (Q6235129). From MaRDI portal. Jump to:navigation, search.

Sparsity, simultaneously to low-rankness, is favored on the subspace matrix by the sophisticated hierarchical Bayesian scheme that is adopted. The proposed ...