• Publications
  • Influence
Modeling TCP throughput: a simple model and its empirical validation
TLDR
A simple analytic characterization of the steady state throughput, as a function of loss rate and round trip time for a bulk transfer TCP flow, i.e., a flow with an unlimited amount of data to send is developed.
Modeling TCP Reno performance: a simple model and its empirical validation
TLDR
A simple analytic characterization of the steady-state send rate as a function of loss rate and round trip time for a bulk transfer TCP flow is developed and is able to more accurately predict TCP send rate and is accurate over a wider range of loss rates.
Analysis and design of controllers for AQM routers supporting TCP flows
TLDR
A recently developed dynamic model of TCP congestion-avoidance mode relates key network parameters such as the number of TCP sessions, link capacity and round-trip time to the underlying feedback control problem and analyzes the present de facto AQM standard: random early detection (RED) and determines that REDs queue-averaging is not beneficial.
Fluid-based analysis of a network of AQM routers supporting TCP flows with an application to RED
TLDR
This paper uses jump process driven Stochastic Differential Equations to model the interactions of a set of TCP flows and Active Queue Management routers in a network setting and presents a critical analysis of the RED algorithm.
A control theoretic analysis of RED
TLDR
This work uses a previously developed nonlinear dynamic model of TCP to analyze and design active queue management (AQM) control systems using random early detection (RED) and presents guidelines for designing linearly stable systems subject to network parameters like propagation delay and load level.
On designing improved controllers for AQM routers supporting TCP flows
TLDR
A previously developed linearized model of TCP and active queue management (AQM) is studied, and the proportional integral (PI) controller is shown to outperform RED significantly.
Diffusion-Convolutional Neural Networks
TLDR
Through the introduction of a diffusion-convolution operation, it is shown how diffusion-based representations can be learned from graph-structured data and used as an effective basis for node classification.
On distinguishing between Internet power law topology generators
  • T. Bu, D. Towsley
  • Computer Science
    Proceedings.Twenty-First Annual Joint Conference…
  • 7 November 2002
TLDR
This work proposes a variation of the recent incremental topology generator of R. Albert and A. Barabasi that is more successful at matching the power law exponent and the clustering behavior of the Internet.
Resisting structural re-identification in anonymized social networks
TLDR
This paper introduces a parameterized model of structural knowledge available to the adversary and quantifies the success of attacks on individuals in anonymized networks, and proposes a novel approach to anonymizing network data that models aggregate network structure and allows analysis to be performed by sampling from the model.
Code red worm propagation modeling and analysis
TLDR
This paper provides a careful analysis of Code Red propagation by accounting for two factors: one is the dynamic countermeasures taken by ISPs and users; the other is the slowed down worm infection rate because Code Red rampant propagation caused congestion and troubles to some routers.
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