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Global Synchronization in Sensornets
 IN PROCEEDINGS OF THE 6TH LATIN AMERICAN SYMPOSIUM ON THEORETICAL INFORMATICS (LATIN’04), PAGES 609–624, BUENOS AIRES
, 2004
"... Time synchronization is necessary in many distributed systems, but achieving synchronization in sensornets, which combine stringent precision requirements with severe resource constraints, is particularly challenging. This challenge has been met by the recent ReferenceBroadcast Synchronization (R ..."
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Time synchronization is necessary in many distributed systems, but achieving synchronization in sensornets, which combine stringent precision requirements with severe resource constraints, is particularly challenging. This challenge has been met by the recent ReferenceBroadcast Synchronization (RBS) proposal, which provides ondemand pairwise synchronization with low overhead and high precision. In this paper we introduce a model of the basic RBS synchronization paradigm. Within the context of this model we characterize the optimally precise clock synchronization algorithm and establish its global consistency. In the
On a new class of bilevel programming problems and its use for reformulating mixedinteger problems
 European Journal of Operations Research
, 1995
"... Abstract: We extend some known results about the Bilevel Linear Problem (BLP), a hierarchical twostage optimization problem, showing how it can be used to reformulate any Mixed Integer (Linear) Problem; then, we introduce some new concepts, which might be useful to fasten almost all the known algor ..."
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Abstract: We extend some known results about the Bilevel Linear Problem (BLP), a hierarchical twostage optimization problem, showing how it can be used to reformulate any Mixed Integer (Linear) Problem; then, we introduce some new concepts, which might be useful to fasten almost all the known algorithms devised for BLP. As this kind of reformulation appears to be somewhat artificial, we define a natural generalization of BLP, the Bilevel Linear/Quadratic Problem (BL/QP), and show that most of the exact and/or approximate algorithms originally devised for the BLP, such as GSA or Kth Best, can be extended to this new class of Bilevel Programming Problems. For BL/QP, more &quot;natural &quot; reformulations of MIPs are available, leading to the use of known (nonexact) algorithms for BLP as (heuristic) approaches to MIPs: we report some contrasting results obtained in the Network Design Problem case, showing that, although the direct application of our (Dual) GSA algorithm is not of any practical use, we obtain as a byproduct a good theoretical characterization of the optimal solutions set of the NDP, along with a powerful scheme for constructing fast algorithms for the Minimum Cost Flow Problem with piecewise convex linear cost functions.
A NETWORK FLOW MODEL FOR FORECASTING AND EVALUATING CRIMINAL DISPLACEMENT
"... In this article, the characteristics of crime patterns in geographic areas over time are described by a network flow model. A method forforecastingfuture crime patterns with the network model is discussed along with procedures for evaluating future displacement by component randomization. An illustr ..."
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In this article, the characteristics of crime patterns in geographic areas over time are described by a network flow model. A method forforecastingfuture crime patterns with the network model is discussed along with procedures for evaluating future displacement by component randomization. An illustrative example of the model building and output analysis from actual arrest data is presented. C’ ubstantial sums of money from federal as well as state and localubstantial government have been allocated to support programs whose goals include the reduction of criminal incidence. In evaluating the effectiveness of such a program, difficulty is often encountered methodologically in the measurement of the effects of a programs ’ individual activities on the programs ’ goal. Recently, crime rates have been modeled as univariate time series models by Deutsch (1978), using the methods of Box and Jenkins (1970). Forms of these models in turn have been used in intervention analysis in order to measure program impact upon crime rates (Deutsch and Alt, 1977, 1976). However, many crime control programs are not targeted in large geographical metropolitan
An EpsilonRelaxation Algorithm for Convex Network Flow Problems
, 1995
"... . A relaxation method for separable convex network flow problems is developed that is wellsuited for problems with large variations in the magnitude of the nonlinear cost terms. The arcs are partitioned into two sets, one of which contains only arcs corresponding to strictly convex costs. The algor ..."
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. A relaxation method for separable convex network flow problems is developed that is wellsuited for problems with large variations in the magnitude of the nonlinear cost terms. The arcs are partitioned into two sets, one of which contains only arcs corresponding to strictly convex costs. The algorithm adjusts flows on the other arcs whenever possible, and terminates with primaldual pairs that satisfy complementary slackness on the strictly convex arc set and fflcomplementary slackness on the remaining arcs. An asynchronous parallel variant of the method is also developed. Computational results demonstrate that the method is significantly more efficient on illconditioned networks than existing methods, solving problems with several thousand nonlinear arcs in one second or less. 1. Introduction. Given a directed graph G(N ; A) with n nodes and m arcs, the minimumcost network flow problem that we consider is: minimize X (i;j)2A f ij (x ij ) subject to X j2ffi + (i) x ij \Gam...
Nonlinear Jacobi And epsilonRelaxation Methods For PARALLEL NETWORK OPTIMIZATION
, 1995
"... In this thesis we develop an efficient decomposition method for largescale convex cost multicommodity network flow problems. The coupling constraints are moved to the objective function via augmented Lagrangian terms. A nonlinear Jacobi algorithm is then used to solve the resulting program in para ..."
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In this thesis we develop an efficient decomposition method for largescale convex cost multicommodity network flow problems. The coupling constraints are moved to the objective function via augmented Lagrangian terms. A nonlinear Jacobi algorithm is then used to solve the resulting program in parallel in a forkjoin manner. Several approaches to solving the coordination problem (corresponding to the join phase) are investigated. In particular, a coordination method is developed that combines excellent parallel efficiency and low communication overhead with a good empirical rate of convergence. Parallel implementations of the algorithm on a Thinking Machines CM5 supercomputer and a cluster of workstations running PVM demonstrate that it is competitive or superior to the best known methods. We are able to solve linear multicommodity problems with over 200,000 variables in less than 15 minutes. The specific form of the nonstrictlyconvex subproblems (corresponding to the fork phase)...