Bounds on the throughput of congestion controllers in the presence of feedback delay
IEEE/ACM Transactions on Networking (TON)
An adaptive virtual queue (AVQ) algorithm for active queue management
IEEE/ACM Transactions on Networking (TON)
Stability of multi-path dual congestion control algorithms
valuetools '06 Proceedings of the 1st international conference on Performance evaluation methodolgies and tools
IEEE/ACM Transactions on Networking (TON)
Time-scale decomposition and equivalent rate-based marking
IEEE/ACM Transactions on Networking (TON)
FluNet: A hybrid internet simulator for fast queue regimes
Computer Networks: The International Journal of Computer and Telecommunications Networking
Network optimization and control
Foundations and Trends® in Networking
Achieving 100% throughput in TCP/AQM under aggressive packet marking with small buffer
IEEE/ACM Transactions on Networking (TON)
Layering as optimization decomposition: questions and answers
MILCOM'06 Proceedings of the 2006 IEEE conference on Military communications
Equilibrium of heterogeneous congestion control: optimality and stability
IEEE/ACM Transactions on Networking (TON)
| Hi-index | 754.84 |
Congestion control algorithms used in the Internet are difficult to analyze or simulate on a large scale, i.e., when there are large numbers of nodes, links, and sources in a network. The reasons for this include the complexity of the actual implementation of the algorithm and the randomness introduced in the packet arrival and service processes due to many factors such as arrivals and departures of sources and uncontrollable short flows in the network. To make the analysis or simulation tractable, often deterministic fluid approximations of these algorithms are used. These approximations are in the form of either deterministic delay differential equations, or more generally, deterministic functional-differential equations (FDEs). In this paper, we ignore the complexity introduced by the window-based implementation of such algorithms and focus on the randomness in the network. We justify the use of deterministic models for proportionally-fair congestion controllers under a limiting regime where the number of flows in a network is large.