On the self-similar nature of Ethernet traffic (extended version)
IEEE/ACM Transactions on Networking (TON)
Wide area traffic: the failure of Poisson modeling
IEEE/ACM Transactions on Networking (TON)
Self-similar traffic and upper bounds to buffer-overflow probability in an ATM queue
Performance Evaluation
Tail probabilities for M/G/\infty input processes (I): Preliminary asymptotics
Queueing Systems: Theory and Applications
Queueing at large resources driven by long-tailed M/G/\infty-modulated processes
Queueing Systems: Theory and Applications
Overflow and losses in a network queue with a self-similar input
Queueing Systems: Theory and Applications
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
Fractal traffic: measurements, modelling and performance evaluation
INFOCOM '95 Proceedings of the Fourteenth Annual Joint Conference of the IEEE Computer and Communication Societies (Vol. 3)-Volume - Volume 3
The War between Mice and Elephants
ICNP '01 Proceedings of the Ninth International Conference on Network Protocols
Snapshot simulation of internet traffic: fast and accurate for heavy-tailed flows
Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops
Performance analysis of a Poisson-Pareto queue over the full range of system parameters
Computer Networks: The International Journal of Computer and Telecommunications Networking
Cluster processes: a natural language for network traffic
IEEE Transactions on Signal Processing
A note on queues with M/G/∞ input
Operations Research Letters
Modeling video traffic using M/G/∞ input processes: a compromise between Markovian and LRD models
IEEE Journal on Selected Areas in Communications
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Simulations involving processes at very different time scales can be so slow to converge that starting in one state and waiting for a representative sample of the state space to be explored is not feasible. Under these circumstances we need to explore a representative range of starting states for a collection of simulations in order to obtain valid results in a reasonable time. Internet traffic is an example of this situation. This is due to the fact that it is made up of clearly identifiable flows and a significant proportion of overall bytes occur in long-lived flows, whose overall duration will in many cases be longer than can be simulated. In this paper we develop a method which constructs a "randomly selected state" of Internet traffic from scratch. This paper explores a technique previously applied to fair queueing and optimized queueing of bottle-necked flows, this time studying the buffering of an aggregation of flows with a common fixed rate (due to limitations of the source or elsewhere along the path of the flow). Direct and importance sampled simulations are validated and compared to an analytical model of the same system.