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Link dimensioning is used by ISPs to properly provision the capacity of theirnetwork links. Operators have to make provisions for sudden traffic bursts andnetwork failures to assure uninterrupted operations. In practice, trafficaverages are used to roughly estimate required capacity. More accuratesolutions often require traffic statistics easily obtained from packetcaptures, e.g. variance. Our investigations on real Internet traffic haveemphasized that the traffic shows high variations at small aggregation times,which indicates that the traffic is self-similar and has a heavy-tailedcharacteristics. Self-similarity and heavy-tailedness are of great importancefor network capacity planning purposes. Traffic modeling process shouldconsider all Internet traffic characteristics. Thereby, the quality of service(QoS) of the network would not affected by any mismatching between the realtraffic properties and the reference statistical model.  This paper proposes a new class of traffic profiles that is better suited formetering bursty Internet traffic streams. We employ bandwidth provisioning todetermine the lowest required bandwidth capacity level for a network link, suchthat for a given traffic load, a desired performance target is met. We validateour approach using packet captures from real IP-based networks.  The proposed link dimensioning approach starts by measuring the statisticalparameters of the available traces, and then the degree of fluctuations in thetraffic has been measured. This is followed by choosing a proper model to fitthe traffic such as lognormal and generalized extreme value distributions.Finally, the optimal capacity for the link can be estimated by deploying thebandwidth provisioning approach. It has been shown that the heavy taileddistributions give more precise values for the link capacity than the Gaussianmodel.

Network Link Dimensioning based on Statistical Analysis and Modeling of Real Internet Traffic