Literature DB >> 33267422

Gaussian Belief Propagation for Solving Network Utility Maximization with Delivery Contracts.

Shengbin Liao1,2, Jianyong Sun3.   

Abstract

Classical network utility maximization (NUM) models fail to capture network dynamics, which are of increasing importance for modeling network behaviors. In this paper, we consider the NUM with delivery contracts, which are constraints to the classical model to describe network dynamics. This paper investigates a method to distributively solve the given problem. We first transform the problem into an equivalent model of linear equations by dual decomposition theory, and then use Gaussian belief propagation algorithm to solve the equivalent issue distributively. The proposed algorithm has faster convergence speed than the existing first-order methods and distributed Newton method. Experimental results have demonstrated the effectiveness of our proposed approach.

Entities:  

Keywords:  Gaussian belief propagation; delivery contracts; distributed algorithms; network utility maximization

Year:  2019        PMID: 33267422      PMCID: PMC7515223          DOI: 10.3390/e21070708

Source DB:  PubMed          Journal:  Entropy (Basel)        ISSN: 1099-4300            Impact factor:   2.524


  1 in total

1.  Correctness of belief propagation in Gaussian graphical models of arbitrary topology.

Authors:  Y Weiss; W T Freeman
Journal:  Neural Comput       Date:  2001-10       Impact factor: 2.026

  1 in total

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