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The Extended Alternating Fractal Renewal Process (EAFRP) model has recently been proposed for modeling the self-similar and impulsive traffic of high-speed networks. For mathematical simplicity, it assumes that the available transmission bandwidth in the network is infinite. In reality, the network has a limit R on the total traffic rate through it, and in addition, the ith user's traffic rate is often limited to special value Li, which is assigned by the bandwidth sharing protocol. We propose a model for single-user traffic, which, by taking into account the aforementioned rate limit Li and R, and in the absence of congestion, provides insight on the distinctive two slope behavior of the loglog survival function of multiuser traffic. For small to medium number of users, such as in local area networks (LANs), the model results in non-Gaussian traffic, whereas as the number of users increases, the resulting traffic is Gaussian, both of which are consistent with real network measurements. We discuss model parameter estimation, provide queuing analysis of the multiple-user traffic model, and, based on real data, show that it achieves a closer approximation of the observed reality than existing models.