Adventures in stochastic processes
Adventures in stochastic processes
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-similarity in World Wide Web traffic: evidence and possible causes
Proceedings of the 1996 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Heavy Tails and Long Range Dependence in On/Off Processes and Associated Fluid Models
Mathematics of Operations Research
On the departure process of a leaky bucket system with long-range dependent input traffic
Queueing Systems: Theory and Applications
A new heavy-tailed discrete distribution for LRD M/G/∞ sample generation
Performance Evaluation
Heavy Tails: The Effect of the Service Discipline
TOOLS '02 Proceedings of the 12th International Conference on Computer Performance Evaluation, Modelling Techniques and Tools
The impact of the service discipline on delay asymptotics
Performance Evaluation - Modelling techniques and tools for computer performance evaluation
Generalized processor sharing with light-tailed and heavy-tailed input
IEEE/ACM Transactions on Networking (TON)
Variable heavy tails in internet traffic
Performance Evaluation - Special issue: Distributed systems performance
How heavy-tailed distributions affect simulation-generated time averages
ACM Transactions on Modeling and Computer Simulation (TOMACS)
The M/G/∞ system revisited: finiteness, summability, long range dependence, and reverse engineering
Queueing Systems: Theory and Applications
Fluid Queues with Heavy-Tailed M/G/∞ Input
Mathematics of Operations Research
Asymptotic analysis of Lévy-driven tandem queues
Queueing Systems: Theory and Applications
Asymptotic behavior of generalized processor sharing queues under subexponential assumptions
Queueing Systems: Theory and Applications
On the flexibility of M/G/∞ processes for modeling traffic correlations
ITC20'07 Proceedings of the 20th international teletraffic conference on Managing traffic performance in converged networks
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A fluid queue with ON periods arriving according to a Poisson process and having a long-tailed distribution has long range dependence. As a result, its performance deteriorates. The extent of this performance deterioration depends on a quantity determined by the average values of the system parameters. In the case when the the performance deterioration is the most extreme, we quantify it by studying the time until the amount of work in the system causes an overflow of a large buffer. This turns out to be strongly related to the tail behavior of the increase in the buffer content during a busy period of the M/G/\infty queue feeding the buffer. A large deviation approach provides a powerful method of studying such tail behavior.