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SIGMETRICS
2008
ACM

Optimal sampling in state space models with applications to network monitoring

11 years 1 months ago
Optimal sampling in state space models with applications to network monitoring
Advances in networking technology have enabled network engineers to use sampled data from routers to estimate network flow volumes and track them over time. However, low sampling rates result in large noise in traffic volume estimates. We propose to combine data on individual flows obtained from sampling with highly aggregate data obtained from SNMP measurements (similar to those used in network tomography) for the tracking problem at hand. Specifically, we introduce a linearized state space model for the estimation of network traffic flow volumes from combined SNMP and sampled data. Further, we formulate the problem of obtaining optimal sampling rates under router resource constraints as an experiment design problem. Theoretically it corresponds to the problem of optimal design for estimation of conditional means for state space models and we present the associated convex programs for a simple approach to it. The usefulness of the approach in the context of network monitoring is illu...
Harsh Singhal, George Michailidis
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2008
Where SIGMETRICS
Authors Harsh Singhal, George Michailidis
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