Optimizing compatible sets in wireless networks through integer programming

In wireless networks, the notion of compatible set refers to a set of radio links that can be simultaneously active with a tolerable interference. Finding a compatible set with maximum weighted revenue from the parallel transmissions is an important optimization subproblem for resource management in...

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Autores principales:	Yuan Li, Michał Pióro, Di Yuan, Jinshu Su
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2014
Materias:	90C11 Mixed integer programming 90B18 Communication networks 68R10 Graph theory Applied mathematics. Quantitative methods T57-57.97 Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/dcc62528eed9485388b5aa60d571e9d7
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id	oai:doaj.org-article:dcc62528eed9485388b5aa60d571e9d7
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spelling	oai:doaj.org-article:dcc62528eed9485388b5aa60d571e9d72021-12-02T05:00:38ZOptimizing compatible sets in wireless networks through integer programming2192-440610.1007/s13675-013-0015-yhttps://doaj.org/article/dcc62528eed9485388b5aa60d571e9d72014-06-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S219244062100023Xhttps://doaj.org/toc/2192-4406In wireless networks, the notion of compatible set refers to a set of radio links that can be simultaneously active with a tolerable interference. Finding a compatible set with maximum weighted revenue from the parallel transmissions is an important optimization subproblem for resource management in wireless networks. For this subproblem, two basic ways of expressing the signal-to-interference-plus-noise-ratio within integer programming are used, differing in the number of variables and the quality of the upper bound given by their linear relaxations. To our knowledge, there is no systematic study comparing the effectiveness of these two approaches to the compatible set optimization problem. The contribution of the article is twofold. First, we present a comparison of the two basic approaches, and, second, we introduce matching inequalities that improve the upper bounds achievable with the two basic approaches. The matching inequalities are generated within the branch-and-cut process using a minimum odd-cut generation procedure based on the Gomory–Hu tree algorithm. The article presents results of a numerical study illustrating our statements and findings.Yuan LiMichał PióroDi YuanJinshu SuElsevierarticle90C11 Mixed integer programming90B18 Communication networks68R10 Graph theoryApplied mathematics. Quantitative methodsT57-57.97Electronic computers. Computer scienceQA75.5-76.95ENEURO Journal on Computational Optimization, Vol 2, Iss 1, Pp 1-15 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	90C11 Mixed integer programming 90B18 Communication networks 68R10 Graph theory Applied mathematics. Quantitative methods T57-57.97 Electronic computers. Computer science QA75.5-76.95
spellingShingle	90C11 Mixed integer programming 90B18 Communication networks 68R10 Graph theory Applied mathematics. Quantitative methods T57-57.97 Electronic computers. Computer science QA75.5-76.95 Yuan Li Michał Pióro Di Yuan Jinshu Su Optimizing compatible sets in wireless networks through integer programming
description	In wireless networks, the notion of compatible set refers to a set of radio links that can be simultaneously active with a tolerable interference. Finding a compatible set with maximum weighted revenue from the parallel transmissions is an important optimization subproblem for resource management in wireless networks. For this subproblem, two basic ways of expressing the signal-to-interference-plus-noise-ratio within integer programming are used, differing in the number of variables and the quality of the upper bound given by their linear relaxations. To our knowledge, there is no systematic study comparing the effectiveness of these two approaches to the compatible set optimization problem. The contribution of the article is twofold. First, we present a comparison of the two basic approaches, and, second, we introduce matching inequalities that improve the upper bounds achievable with the two basic approaches. The matching inequalities are generated within the branch-and-cut process using a minimum odd-cut generation procedure based on the Gomory–Hu tree algorithm. The article presents results of a numerical study illustrating our statements and findings.
format	article
author	Yuan Li Michał Pióro Di Yuan Jinshu Su
author_facet	Yuan Li Michał Pióro Di Yuan Jinshu Su
author_sort	Yuan Li
title	Optimizing compatible sets in wireless networks through integer programming
title_short	Optimizing compatible sets in wireless networks through integer programming
title_full	Optimizing compatible sets in wireless networks through integer programming
title_fullStr	Optimizing compatible sets in wireless networks through integer programming
title_full_unstemmed	Optimizing compatible sets in wireless networks through integer programming
title_sort	optimizing compatible sets in wireless networks through integer programming
publisher	Elsevier
publishDate	2014
url	https://doaj.org/article/dcc62528eed9485388b5aa60d571e9d7
work_keys_str_mv	AT yuanli optimizingcompatiblesetsinwirelessnetworksthroughintegerprogramming AT michałpioro optimizingcompatiblesetsinwirelessnetworksthroughintegerprogramming AT diyuan optimizingcompatiblesetsinwirelessnetworksthroughintegerprogramming AT jinshusu optimizingcompatiblesetsinwirelessnetworksthroughintegerprogramming
_version_	1718400859813969920

Optimizing compatible sets in wireless networks through integer programming

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