Fluid-based analysis of a network of AQM routers supporting TCP flows with an application to RED

By Vishal Misra, W. Gong, D. Towsley. Conference on Applications, Technologies, Architectures, and Protocols for Computer Communication, 2000

1,538 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/399018214db937bdad918dc1653993cea986ccc1

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Steven H. Low
2. Rayadurgam Srikant
3. John C. Doyle
4. Fernando Paganini
5. Srisankar S. Kunniyur
6. Sanjay Shakkottai
7. Senior Member
8. Christopher V. Hollot

In Electrical and Electronic Engineering

1. Steven H. Low
2. John C. Doyle
3. Rayadurgam Srikant
4. Fernando Paganini
5. Srisankar S. Kunniyur
6. Christopher V. Hollot
7. Sanjay Shakkottai
8. D. Towsley

Citations in the corpus

• An adaptive virtual queue (AVQ) algorithm for active queue management (2004, methodology): “d ; where Wi is the window-size of user i; we recover the TCP window control algorithm [6, 3 ].”
• Analysis and design of controllers for AQM routers supporting TCP flows (2002, methodology): “The launching point for this paper is a fluid-flow model of TCP behavior developed in [17].”
• Passive estimation of TCP round-trip times (2002, background): “An estimate of the TCP RTTs is also useful in the configuration of active queue management modules [13], and in the identification of congestion unresponsive traffic [7, 11].”
• PIE: A lightweight control scheme to address the bufferbloat problem (2013, background): “It is shown in [14] that the TCP window evolution can be approximated as”
• Scalable laws for stable network congestion control (2001, methodology): “In terms of the dynamics of TCP, very recently an analytical model has been developed [18] that correlates well with standard simulators, and allows for stability studies [5].”
• Internet congestion control (2002, background): “In fact, by incorporating explicit measures of congestion, recent analysis [21], [22] has shown that the predominant TCP implementation (called Reno) and its variants are prone to instabilities when combined with network delays and, more surprisingly, with increases in network capacity.”
• Analysis and design of an adaptive virtual queue (AVQ) algorithm for active queue management (2001, methodology): “Also, note that on substituting xi ≈ Wi d , where Wi is the window-size of user i, we recover the TCP window control algorithm [11, 14].”
• A control theoretic analysis of RED (2001, methodology): “In [9], a dynamic model of TCP behavior was developed using fluid-flow and stochastic differential equation analysis.”
• Multi-Path TCP: A Joint Congestion Control and Routing Scheme to Exploit Path Diversity in the Internet (2006, methodology): “In particular, the stability aspects of the packet model are predicted well by flu id models [19, 8, 21, 3, 4].”
• End-to-end congestion control schemes: utility functions, random losses and ECN marks (2000, background): “A more precise model would account for feedback delay; we refer the interested reader to [16] and [25].”
• Code red worm propagation modeling and analysis (2002, methodology): “In this paper, However, we treat the worm propagation as a continuous process and use the continuous differential equation (9) to describe it. Such an approximation is accurate for large-scale system and is widely used in epidemic modeling [15], Internet traffic fluid modeling [ 26 ], etc.”
• End-to-end congestion control for the internet: delays and stability (2001, background): “[21]), as well as priority mechanisms at the routers to provide support for differentiated services (see, e.”