Abstract
Network monitoring applications (e.g., anomaly detection and traffic classification) are among the first sources of big data. With the advent of algorithms and frameworks able to handle datasets of unprecedented scales, researchers and practitioners have the opportunity to face network monitoring problems with novel data-driven approaches. This section summarizes the state of the art on the use of big data approaches for network monitoring. It describes why network monitoring is a big data problem and how the big data approaches are assisting on network monitoring tasks. Open research directions are then highlighted.
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