Open AccessApplication of Improved Multi-Objective Bacterial Foraging Algorithm in Virtual Network Mapping Algorithm
Author(s) -
Yihui Qu,
Jun Li
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1237/2/022099
Subject(s) - algorithm , computer science , node (physics) , virtual network , function (biology) , out of kilter algorithm , stability (learning theory) , resource (disambiguation) , mathematical optimization , mathematics , distributed computing , theoretical computer science , shortest path problem , engineering , dijkstra's algorithm , graph , computer network , structural engineering , evolutionary biology , machine learning , biology
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.