revisiting the case for a minimalist approach for network flow monitoring
Network management applications require accurate estimates of a wide range of flow-level traffic metrics. Given the inadequacy of current packet-sampling-based solutions, several application-specific monitoring algorithms have emerged. While these provide better accuracy for the specific applications they target, they increase router complexity and require vendors to commit to hardware primitives without knowing how useful they will be to meet the needs of future applications. In this paper, we show using trace-driven evaluations that such complexity and early commitment may not be necessary. We revisit the case for a "minimalist" approach in which a small number of simple yet generic router primitives collect flow-level data from which different traffic metrics can be estimated. We demonstrate the feasibility and promise of such a minimalist approach using flow sampling and sample-and-hold as sampling primitives and configuring these in a network-wide coordinated fashion using cSamp. We show that this proposal yields better accuracy across a collection of application-level metrics than dividing the same memory resources across metric-specific algorithms. Moreover, because a minimalist approach enables late binding to what application level metrics are important, it better insulates router implementations and deployments from changing monitoring needs.
sampling anomaly detection traffic monitoring data streaming