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In order to provision bandwidth, in this paper we propose a discrete-time dynamical system model to capture the marginal distribution and autocorrelation of the input traffic simultaneously. For model identification, we use a periodicity transform to identify the most significant periods of the traffic and use an auto regressive time series to model it. Bandwidth provisioning is formulated as an optimal...
Bandwidth provisioning is an important issue for Internet service providers (ISPs) and ensuring quality of service (QoS) is a major concern. QoS is closely related to the available bandwidth which itself is subject to financial constraints. Unfortunately, up to now there have been no adequate tools available in the market so that ISPs can do accurate bandwidth provisioning. In this paper, we describe...
This paper develops formulas to provision bandwidth for any number of high speed internet subscribers at a given probability that load exceeds available capacity. Formulas are based on Gamma models fitted to traffic loads generated over 1-sec intervals by various subscriber aggregations. We assume loads are i.i.d. and use characteristic function properties to extrapolate load distributions for any...
Dynamic bandwidth provisioning for data service is an efficient way to optimize network resource utilization. For the purpose of dynamical bandwidth provisioning, we need a model that can capture online the traffic characteristics and facilitate mathematical analysis. A mixture of gamma distributions can approximate any distribution with nonnegative support as closely as desired. It can not only characterize...
For the purpose of provisioning bandwidth for Internet access, we need to model the traffic at large time scales, over which the traffic shows evident periodicity, long correlation and a non-Gaussian marginal distribution. To capture these characteristics simultaneously, in this paper we use a periodicity transform-to identify the most significant periods of the traffic and use an autoregressive time...
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