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Open AccessArticle

Gaussian Belief Propagation for Solving Network Utility Maximization with Delivery Contracts

1
National Engineering Center for E-Learning, Huazhong Normal University, Wuhan 430079, China
2
The National Engineering Laboratory for Educational Big Data Technology, Huazhong Normal University, Wuhan 430079, China
3
The National Engineering Laboratory for Big Data Analytics and The School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an 710049, China
*
Author to whom correspondence should be addressed.
Entropy 2019, 21(7), 708; https://doi.org/10.3390/e21070708
Received: 13 June 2019 / Revised: 13 July 2019 / Accepted: 17 July 2019 / Published: 19 July 2019
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PDF [253 KB, uploaded 19 July 2019]
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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. View Full-Text
Keywords: network utility maximization; delivery contracts; Gaussian belief propagation; distributed algorithms network utility maximization; delivery contracts; Gaussian belief propagation; distributed algorithms
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Liao, S.; Sun, J. Gaussian Belief Propagation for Solving Network Utility Maximization with Delivery Contracts. Entropy 2019, 21, 708.

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