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An Ant Colony Optimization Algorithm for Virtual Network Embedding

机译:一种虚拟网络嵌入的蚁群优化算法

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Virtual network embedding that embedding virtual network in substrate network is usually mentioned as resource allocation problem in network virtualization. Virtual network embedding can be employed to solve the problems like resource constraint, access control, request online and diversity of topology. This paper develops an ant colony optimization algorithm of virtual network embedding (ACO-VNE). The ants secrete and update pheromones in node mapping according to the cost of link mapping. Based on feedback information, the ants move to find good solution through learning from each other. Simulation results suggest that the algorithm can map the virtual network with low rejection rate and high revenue of substrate network.
机译:嵌入嵌入基板网络中的虚拟网络的虚拟网络通常被称为网络虚拟化中的资源分配问题。可以采用虚拟网络嵌入来解决资源约束,访问控制,在线和拓扑多样性等问题。本文开发了虚拟网络嵌入(ACO-VNE)的蚁群优化算法。根据链接映射的成本,蚂蚁在节点映射中分泌和更新信息素。根据反馈信息,蚂蚁通过彼此学习来寻找良好的解决方案。仿真结果表明,该算法可以用低拒绝率和基板网络的高收入来映射虚拟网络。

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