Dynamics of IP traffic: a study of the role of variability and the impact of control
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Statistical bandwidth sharing: a study of congestion at flow level
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
Performance evaluation of a queue fed by a Poisson Pareto burst process
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Advances in modeling and engineering of Longe-Range dependent traffic
On the relationship between file sizes, transport protocols, and self-similar network traffic
ICNP '96 Proceedings of the 1996 International Conference on Network Protocols (ICNP '96)
Congestion at flow level and the impact of user behaviour
Computer Networks: The International Journal of Computer and Telecommunications Networking
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
QoS-aware bandwidth provisioning for IP network links
Computer Networks: The International Journal of Computer and Telecommunications Networking
Equivalent capacity and its application to bandwidth allocation in high-speed networks
IEEE Journal on Selected Areas in Communications
Dimensioning network links: a new look at equivalent bandwidth
IEEE Network: The Magazine of Global Internetworking
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Future network components will power down unused resources to save energy. Thereto, they need to determine the required capacity by observing the traffic. In this paper, we propose a light-weight estimator for the relevant parameters of aggregated packet traffic. The estimator assumes an M/G/∞ traffic model on flow level, which has been proposed for aggregated Internet traffic. We find that the variation of the aggregate traffic rate is defined by the bit rate of contributing application streams, i.e. traffic bursts triggered by end-user applications. We identify the effect of these streams on the variance-time behavior of the aggregated traffic rate. From this, we derive an estimator for the application stream bit rate based on second-order statistics of the aggregate rate. Simulation results for inelastic and TCP traffic show a good stream rate estimation accuracy, provided that the measuring period is sufficient to capture the variance of the aggregate rate.