A Distributed Algorithm for Random Convex Programming

Abstract : We study a distributed approach for solving random convex programs (RCP) for the case in which problem constraints are distributed among nodes in a processor network. We devise a distributed algorithm that allows network nodes to reach consensus on problem solution by exchanging a local set of constraints at each iteration. We prove that the algorithm assures finite-time convergence to problem solution and we provide explicit bounds on the maximum number of constraints to be exchanged among nodes at each communication round. Numerical experiments confirm the theoretical derivation and show that a parallel implementation of the proposed approach speeds-up the solution of the RCP with respect to centralized computation.
Type de document :
Communication dans un congrès
Roberto Cominetti and Sylvain Sorin and Bruno Tuffin. NetGCOOP 2011 : International conference on NETwork Games, COntrol and OPtimization, Oct 2011, Paris, France. IEEE, 2011
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Dernière modification le : lundi 20 juin 2016 - 14:10:32
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  • HAL Id : hal-00644380, version 1

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Luca Carlone, Vaibhav Srivastava, Francesco Bullo, Giuseppe Calafiore. A Distributed Algorithm for Random Convex Programming. Roberto Cominetti and Sylvain Sorin and Bruno Tuffin. NetGCOOP 2011 : International conference on NETwork Games, COntrol and OPtimization, Oct 2011, Paris, France. IEEE, 2011. 〈hal-00644380〉

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