Computational complexity of loss networks
Theoretical Computer Science - Special issue on probabilistic modelling
SIGMETRICS '97 Proceedings of the 1997 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Dimensioning bandwidth for elastic traffic in high-speed data networks
IEEE/ACM Transactions on Networking (TON)
A game theoretic framework for bandwidth allocation and pricing in broadband networks
IEEE/ACM Transactions on Networking (TON)
Understanding TCP Vegas: a duality model
Journal of the ACM (JACM)
Insensitive Bandwidth Sharing in Data Networks
Queueing Systems: Theory and Applications
Calculating the flow level performance of balanced fairness in tree networks
Performance Evaluation
A queueing analysis of max-min fairness, proportional fairness and balanced fairness
Queueing Systems: Theory and Applications
Insensitive Traffic Models for Communication Networks
Discrete Event Dynamic Systems
Insensitive, maximum stable allocations converge to proportional fairness
Queueing Systems: Theory and Applications
Congestion in large balanced multirate links
Proceedings of the 23rd International Teletraffic Congress
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In this paper, we obtain analytical approximations for various performance measures for a large fluid stochastic network that operates under a balanced fair bandwidth allocation policy. Balanced fairness results in the insensitivity of the stationary distribution of the number in the system to the precise distribution of file sizes. Balanced fairness has been shown to coincide with proportional fairness in large systems. The model we consider is that of servers operating under balanced fair rate allocations that are accessed by a large number of independent heterogeneous flows characterized by their arrival rate and general distributions of the file sizes; and a maximum service rate associated with each type of flow. The largeness of the system is parameterized by a scaling parameter that scales the arrival rates and capacity in such a way that the ratio is fixed. By exploiting a connection of the congestion probabilities with multirate Erlang loss systems, we use local limit large deviation methods to obtain accurate approximations as the scaling increases. The paper first discusses the single link case which is then extended to the case of a parking lot model that is a special case of tree networks.