VNE-AFS：基于人工鱼群的网络虚拟化映射算法

虚拟网络资源映射是云计算研究领域的一个难点问题。以降低底层网络映射开销为目标，提出一种基于人工鱼群的网络虚拟化映射算法VNE-AFS。根据虚拟网络请求对底层网络节点和链路的约束关系建立二进制组合优化模型，并利用人工鱼群算法实现虚拟网络资源向底层网络资源的近似最优映射。实验结果表明，与现有的虚拟网络映射算法相比，该算法有效地降低了底层网络的开销和求解时间，提高了虚拟网络映射的成功率、平均收益和资源利用率。

VNE-AFS:virtual network embedding based on artificial fish swarm

Recently virtual network embedding problem had been proposed as a research challenge in the cloud computing environment.In order to reduce the costs,a virtual network embedding algorithms based on artificial fish swarm(VNE-AFS)was proposed.A binary combinatorial optimization model was built according to the constraints on nodes and links between virtual network and substrate network,and the artificial fish swarm algorithm was used to achieve the approximate optimal mapping.The simulation results indicate that the costs of substrate network and computation time are reduced and the success rate,average revenue of embedding and average usage of links are increased compared with the existing virtual network embedding algorithms.