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A distributed transportation simplex applied to a Content Distribution Network problem

Rafaelli de C. Coutinho, Lúcia M. A. Drummond, Yuri Frota (2014)

RAIRO - Operations Research - Recherche Opérationnelle

A Content Distribution Network (CDN) can be defined as an overlay system that replicates copies of contents at multiple points of a network, close to the final users, with the objective of improving data access. CDN technology is widely used for the distribution of large-sized contents, like in video streaming. In this paper we address the problem of finding the best server for each customer request in CDNs, in order to minimize the overall cost. We consider the problem as a transportation problem...

A distributed voting scheme to maximize preferences

Peter Auer, Nicolò Cesa-Bianchi (2006)

RAIRO - Theoretical Informatics and Applications

We study the problem of designing a distributed voting scheme for electing a candidate that maximizes the preferences of a set of agents. We assume the preference of agent i for candidate j is a real number xi,j, and we do not make any assumptions on the mechanism generating these preferences. We show simple randomized voting schemes guaranteeing the election of a candidate whose expected total preference is nearly the highest among all candidates. The algorithms we consider are designed so that...

A weighted HP model for protein folding with diagonal contacts

Hans-Joachim Böckenhauer, Dirk Bongartz (2007)

RAIRO - Theoretical Informatics and Applications

The HP model is one of the most popular discretized models for attacking the protein folding problem, i.e., for the computational prediction of the tertiary structure of a protein from its amino acid sequence. It is based on the assumption that interactions between hydrophobic amino acids are the main force in the folding process. Therefore, it distinguishes between polar and hydrophobic amino acids only and tries to embed the amino acid sequence into a two- or three-dimensional grid lattice...

Distributed aggregative optimization with quantized communication

Ziqin Chen, Shu Liang (2022)

Kybernetika

In this paper, we focus on an aggregative optimization problem under the communication bottleneck. The aggregative optimization is to minimize the sum of local cost functions. Each cost function depends on not only local state variables but also the sum of functions of global state variables. The goal is to solve the aggregative optimization problem through distributed computation and local efficient communication over a network of agents without a central coordinator. Using the variable tracking...

Distributed optimization for multi-agent system over unbalanced graphs with linear convergence rate

Songsong Cheng, Shu Liang (2020)

Kybernetika

Distributed optimization over unbalanced graphs is an important problem in multi-agent systems. Most of literatures, by introducing some auxiliary variables, utilize the Push-Sum scheme to handle the widespread unbalance graph with row or column stochastic matrix only. But the introduced auxiliary dynamics bring more calculation and communication tasks. In this paper, based on the in-degree and out-degree information of each agent, we propose an innovative distributed optimization algorithm to reduce...

Event-Based Proof of the Mutual Exclusion Property of Peterson’s Algorithm

Ievgen Ivanov, Mykola Nikitchenko, Uri Abraham (2015)

Formalized Mathematics

Proving properties of distributed algorithms is still a highly challenging problem and various approaches that have been proposed to tackle it [1] can be roughly divided into state-based and event-based proofs. Informally speaking, state-based approaches define the behavior of a distributed algorithm as a set of sequences of memory states during its executions, while event-based approaches treat the behaviors by means of events which are produced by the executions of an algorithm. Of course, combined...

Hitting time of a corner for a reflected diffusion in the square

F. Delarue (2008)

Annales de l'I.H.P. Probabilités et statistiques

We discuss the long time behavior of a two-dimensional reflected diffusion in the unit square and investigate more specifically the hitting time of a neighborhood of the origin. We distinguish three different regimes depending on the sign of the correlation coefficient of the diffusion matrix at the point 0. For a positive correlation coefficient, the expectation of the hitting time is uniformly bounded as the neighborhood shrinks. For a negative one, the expectation explodes in a polynomial way...

Multi-agent network flows that solve linear complementarity problems

Shu Liang, Xianlin Zeng (2018)

Kybernetika

In this paper, we consider linear complementarity problems with positive definite matrices through a multi-agent network. We propose a distributed continuous-time algorithm and show its correctness and convergence. Moreover, with the help of Kalman-Yakubovich-Popov lemma and Lyapunov function, we prove its asymptotic convergence. We also present an alternative distributed algorithm in terms of an ordinary differential equation. Finally, we illustrate the effectiveness of our method by simulations....

Multi-agent solver for non-negative matrix factorization based on optimization

Zhipeng Tu, Weijian Li (2021)

Kybernetika

This paper investigates a distributed solver for non-negative matrix factorization (NMF) over a multi-agent network. After reformulating the problem into the standard distributed optimization form, we design our distributed algorithm (DisNMF) based on the primal-dual method and in the form of multiplicative update rule. With the help of auxiliary functions, we provide monotonic convergence analysis. Furthermore, we show by computational complexity analysis and numerical examples that our distributed...

Solving maximum independent set by asynchronous distributed hopfield-type neural networks

Giuliano Grossi, Massimo Marchi, Roberto Posenato (2006)

RAIRO - Theoretical Informatics and Applications

We propose a heuristic for solving the maximum independent set problem for a set of processors in a network with arbitrary topology. We assume an asynchronous model of computation and we use modified Hopfield neural networks to find high quality solutions. We analyze the algorithm in terms of the number of rounds necessary to find admissible solutions both in the worst case (theoretical analysis) and in the average case (experimental Analysis). We show that our heuristic is better than the...

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