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Experience in Measuring Backbone Traffic Variability: Models, Metrics, Measurements and Meaning

Experience in Measuring Backbone Traffic Variability: Models, Metrics, Measurements and Meaning. NETREAD UC Berkeley George Porter Oct 4, 2002. Goals. Modeling backbone links Don’t want to do per-packet traces They propose new metric, the “peakedness” parameter

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Experience in Measuring Backbone Traffic Variability: Models, Metrics, Measurements and Meaning

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  1. Experience in Measuring Backbone Traffic Variability: Models, Metrics, Measurements and Meaning NETREAD UC Berkeley George Porter Oct 4, 2002

  2. Goals • Modeling backbone links • Don’t want to do per-packet traces • They propose new metric, the “peakedness” parameter • This can be derived from SNMP data • Answer question: “should we use dynamically arranged optical links?”

  3. Planning Traffic engineering SLAs overprovisioning Usefulness

  4. Peakedness Parameter • “provides a measure of the traffic variability” • One parameter needed to measure stochastic variation in traffic • A good value is 0.5-3.0Mbs for 5 minutes? • No definition, no mention how to calculate this • !?

  5. Gravity Model • Used to infer traffic matrix • For cities: • Strength of interaction between cities proportional to the product of the populations divided by the distance squared. • For network: • Fraction of traffic entering/leaving to/from each region

  6. Observations • Traffic is regular and predictable • Large deviations from predications are rare • a can be big for no reason • Argument for dynamically provisioned optical links weak

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