16,161 research outputs found
A duality model of TCP and queue management algorithms
We propose a duality model of end-to-end congestion control and apply it to understanding the equilibrium properties of TCP and active queue management schemes. The basic idea is to regard source rates as primal variables and congestion measures as dual variables, and congestion control as a distributed primal-dual algorithm over the Internet to maximize aggregate utility subject to capacity constraints. The primal iteration is carried out by TCP algorithms such as Reno or Vegas, and the dual iteration is carried out by queue management algorithms such as DropTail, RED or REM. We present these algorithms and their generalizations, derive their utility functions, and study their interaction
Convex Relaxation of Optimal Power Flow, Part II: Exactness
This tutorial summarizes recent advances in the convex relaxation of the
optimal power flow (OPF) problem, focusing on structural properties rather than
algorithms. Part I presents two power flow models, formulates OPF and their
relaxations in each model, and proves equivalence relations among them. Part II
presents sufficient conditions under which the convex relaxations are exact.Comment: Citation: IEEE Transactions on Control of Network Systems, June 2014.
This is an extended version with Appendex VI that proves the main results in
this tutoria
Convex Relaxation of Optimal Power Flow, Part I: Formulations and Equivalence
This tutorial summarizes recent advances in the convex relaxation of the
optimal power flow (OPF) problem, focusing on structural properties rather than
algorithms. Part I presents two power flow models, formulates OPF and their
relaxations in each model, and proves equivalence relations among them. Part II
presents sufficient conditions under which the convex relaxations are exact.Comment: Citation: IEEE Transactions on Control of Network Systems,
15(1):15-27, March 2014. This is an extended version with Appendices VIII and
IX that provide some mathematical preliminaries and proofs of the main
result
Estimating Euler equations
In this paper we consider conditions under which the estimation of a log-linearized Euler equation for
consumption yields consistent estimates of preference parameters. When utility is isoelastic and a
sample covering a long time period is available, consistent estimates are obtained from the loglinearized
Euler equation when the innovations to the conditional variance of consumption growth are
uncorrelated with the instruments typically used in estimation.
We perform a Montecarlo experiment, consisting in solving and simulating a simple life cycle model
under uncertainty, and show that in most situations, the estimates obtained from the log-linearized
equation are not systematically biased. This is true even when we introduce heteroscedasticity in the
process generating income.
The only exception is when discount rates are very high (e.g. 47% per year). This problem arises
because consumers are nearly always close to the maximum borrowing limit: the estimation bias is
unrelated to the linearization and estimates using nonlinear GMM are as bad. Across all our situations,
estimation using a log-linearized Euler equation does better than nonlinear GMM despite the absence
of measurement error.
Finally, we plot life cycle profiles for the variance of consumption growth, which, except when the
discount factor is very high, is remarkably flat. This implies that claims that demographic variables in
log-linearized Euler equations capture changes in the variance of consumption growth are unwarranted
Reverse Engineering TCP/IP-like Networks using Delay-Sensitive Utility Functions
TCP/IP can be interpreted as a distributed primal-dual algorithm to maximize aggregate utility over source rates. It has recently been shown that an equilibrium of TCP/IP, if it exists, maximizes the same delay-insensitive utility over both source rates and routes, provided pure congestion prices are used as link costs in the shortest-path calculation of IP. In practice, however, pure dynamic routing is never used and link costs are weighted sums of both static as well as dynamic components. In this paper, we introduce delay-sensitive utility functions and identify a class of utility functions that such a TCP/IP equilibrium optimizes. We exhibit some counter-intuitive properties that any class of delay-sensitive utility functions optimized by TCP/IP necessarily possess. We prove a sufficient condition for global stability of routing updates for general networks. We construct example networks that defy conventional wisdom on the effect of link cost parameters on network stability and utility
Simulation comparison of RED and REM
We propose earlier an optimization based low control for the Internet called Random Exponential Marking (REM). REM consists of a link algorithm, that probabilistically marks packets inside the network, and a source algorithm, that adapts source rate to observed marking. The marking probability is exponential in a link congestion measure, so that the end-to-end marking probability is exponential in a path congestion measure. Because of the finer measure of congestion provided by REM, sources do not constantly probe the network for spare capacity, but settle around a globally optimal equilibrium, thus avoiding the perpetual cycle of sinking into and recovering from congestion. In this paper we compare the performance of REM with Reno over RED through simulation
Convex Relaxations and Linear Approximation for Optimal Power Flow in Multiphase Radial Networks
Distribution networks are usually multiphase and radial. To facilitate power
flow computation and optimization, two semidefinite programming (SDP)
relaxations of the optimal power flow problem and a linear approximation of the
power flow are proposed. We prove that the first SDP relaxation is exact if and
only if the second one is exact. Case studies show that the second SDP
relaxation is numerically exact and that the linear approximation obtains
voltages within 0.0016 per unit of their true values for the IEEE 13, 34, 37,
123-bus networks and a real-world 2065-bus network.Comment: 9 pages, 2 figures, 3 tables, accepted by Power System Computational
Conferenc
Decomposing changes in income risk using consumption data
This paper concerns the decomposition of income risk into permanent and transitory components using repeated cross-section data on income and consumption. Our focus is on the detection of changes in the magnitudes of variances of permanent and transitory risks. A new approximation to the optimal consumption growth rule is developed.
Evidence from a dynamic stochastic simulation is used to show that this approximation can provide a robust method for decomposing income risk in a nonstationary environment. We examine robustness to unobserved heterogeneity in consumption growth and to unobserved heterogeneity in income growth. We use this approach to investigate the growth in income inequality in the UK in the 1980s
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