Simulated annealing based resource allocation for cloud data centers
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Green cloud virtual network provisioning based ant colony optimization
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Performance evaluation of artificial intelligence algorithms for virtual network embedding
Engineering Applications of Artificial Intelligence
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The virtual network embedding (VNE) problem deals with the embedding of virtual network (VN) requests in an underlying physical (substrate network) infrastructure. When both the node and link constraints are considered, the VN embedding problem is NP-hard, even in the offline case. The genetic algorithm (GA) is an excellent approach to solving complex problems in optimization with difficult constraints. This paper explores applying GA to handle the VNE problem. We propose two GA-based VNE algorithms and evaluate them by comparing with the existing state-of-the-art VNE algorithms, including PSO-based VNE approaches. Extensive simulation results validate the capability of the proposed GA-based VNE algorithms in terms of the InP long-term revenue and the VN embedding cost.