Application of Improved Multi-Objective Bacterial Foraging Algorithm in Virtual Network Mapping Algorithm

For the virtual network mapping problem, consideration of many aspects will be more comprehensive. In this paper, the multi-objective bacterial foraging optimization algorithm is improved to solve this problem. First, because the virtual network mapping problem is a discrete problem, the operator of...

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Published inJournal of physics. Conference series Vol. 1237; no. 2; pp. 22099 - 22106
Main Authors Qu, Yihui, Li, Jun
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.06.2019
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ISSN1742-6588
1742-6596
1742-6596
DOI10.1088/1742-6596/1237/2/022099

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Abstract For the virtual network mapping problem, consideration of many aspects will be more comprehensive. In this paper, the multi-objective bacterial foraging optimization algorithm is improved to solve this problem. First, because the virtual network mapping problem is a discrete problem, the operator of the algorithm is redefined as discrete; secondly, the resource congestion factor and 2-opt algorithm are introduced in the chemotaxis operation of the algorithm, and the cross-factor is introduced in the copy operation, so that the found solution is better. At the same time, the node resource load balance degree and the minimum cost are used as the fitness function, so that the found solution solves the problem more. The experimental results show that the algorithm is used to solve the virtual network mapping problem. The algorithm has good validity and stability in both large-scale virtual network requests and standard cases.
AbstractList For the virtual network mapping problem, consideration of many aspects will be more comprehensive. In this paper, the multi-objective bacterial foraging optimization algorithm is improved to solve this problem. First, because the virtual network mapping problem is a discrete problem, the operator of the algorithm is redefined as discrete; secondly, the resource congestion factor and 2-opt algorithm are introduced in the chemotaxis operation of the algorithm, and the cross-factor is introduced in the copy operation, so that the found solution is better. At the same time, the node resource load balance degree and the minimum cost are used as the fitness function, so that the found solution solves the problem more. The experimental results show that the algorithm is used to solve the virtual network mapping problem. The algorithm has good validity and stability in both large-scale virtual network requests and standard cases.
For the virtual network mapping problem, consideration of many aspects will be more comprehensive. In this paper, the multi-objective bacterial foraging optimization algorithm is improved to solve this problem. First, because the virtual network mapping problem is a discrete problem, the operator of the algorithm is redefined as discrete; secondly, the resource congestion factor and 2- opt algorithm are introduced in the chemotaxis operation of the algorithm, and the cross-factor is introduced in the copy operation, so that the found solution is better. At the same time, the node resource load balance degree and the minimum cost are used as the fitness function, so that the found solution solves the problem more. The experimental results show that the algorithm is used to solve the virtual network mapping problem. The algorithm has good validity and stability in both large-scale virtual network requests and standard cases.
Author Li, Jun
Qu, Yihui
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Cites_doi 10.1109/MCOM.2009.5183468
10.1109/SURV.2013.013013.00155
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SubjectTerms Algorithms
Mapping
Minimum cost
Multiple objective analysis
Optimization
Virtual networks
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