Apparatus and method for congestion control in high speed networks

An adjustable bit rate (ABR) feedback control scheme is provided where the effects of multiloop delays and high priority traffic transmission are built into the control model. The data traffic is filtered by a low pass filter. Then, the low frequency bandwidth of the filtered traffic is measured and compared to a predetermined threshold. If the measured value exceeds the threshold, the ABR traffic flow is reduced. If the measured value is less than the threshold, the ABR traffic flow is increased. In addition, a General Prediction Control (GPC) method may be applied to the control model for optimal performance. An object of the invention is to minimize the unused link capacity subject to no congestion, where the ABR traffic is adapted to the low frequency variation of high priority traffic flow for high efficiency.Board of Regents, University of Texas Syste

Local observers on linear Lie groups with linear estimation error dynamics

This paper proposes local exponential observers for systems on linear Lie groups. We study two different classes of systems. In the first class, the full state of the system evolves on a linear Lie group and is available for measurement. In the second class, only part of the system's state evolves on a linear Lie group and this portion of the state is available for measurement. In each case, we propose two different observer designs. We show that, depending on the observer chosen, local exponential stability of one of the two observation error dynamics, left- or right-invariant error dynamics, is obtained. For the first class of systems these results are developed by showing that the estimation error dynamics are differentially equivalent to a stable linear differential equation on a vector space. For the second class of system, the estimation error dynamics are almost linear. We illustrate these observer designs on an attitude estimation problem

An enhanced random early marking algorithm for Internet flow control

We propose earlier an optimization based flow control for the Internet called Random Early Marking (REM). In this paper we propose and evaluate an enhancement that attempts to speed up the convergence of REM in the face of large feedback delays. REM can be regarded as an implementation of an optimization algorithm in a distributed network. The basic idea is to treat the optimization algorithm as a discrete time system and apply linear control techniques to stabilize its transient. We show that the modified algorithm is stable globally and converges exponentially locally. This algorithm translates into an enhanced REM scheme and we illustrate the performance improvement through simulation

Is Inflation Persistence Over?

We analyze inflation persistence in several industrial and emerging countries in the recent past by estimating reduced-form models of inflation dynamics. We select a very representative group of 23 industrial and 17 emerging economies. Our sample period is comprised of quarterly data and starts in the first quarter of 1995. Our results show that inflation persistence is low and stable for all countries in our sample. It seems to be lower in industrial relative to emerging countries. Finally, even countries that have had “hyperinflation” experience in the recent past showed low levels of inflation persistence, albeit apparently higher than the other countries in our sample.

Evolution of Tax Evasion

In this paper we analyze a tax evasion game with taxpayer learning by imitation. If the authority commits to a fixed auditing probability, a positive share of cheating is obtained in equilibrium. This stands in contrast to the existing literature that yields full compliance of audited taxpayer who are rational, have a lot of information and thus do not need to interact. When the authority adjusts auditing probability every period, cycling in cheating-auditing occurs. Thus, the real life phenomenon of compliance fluctuations is explained within the model rather than by exogenous parameter shifts.tax evasion; imitation; learning