针对大规模虚拟网络映射算法映射效率低、在映射节点和链路时易引起网络分割等问题，提出了一种图的邻接分割方法，将虚拟网络分割为多个邻接的星型结构，以简化虚拟网络映射规模；建立了一种节点和链路的资源匹配模型，使节点映射能适应链路资源分布状态、链路映射能匹配节点可用资源大小，从而协调完成节点和链路映射操作，解决节点、链路的映射协调性差以及网络资源分配不匹配等问题 . 仿真实验结果表明，所提出的算法降低了虚拟链路的映射路径长度，提高了虚拟网络映射效率和负载均衡性能，获得了较高的虚拟网络请求接受率 。

As the existing mapping algorithms of large-scale virtual networks are of low execution efficiency and are prone to network partition when mapping virtual nodes and links ， a method of graph adjacency segmentation is proposed ， which decomposes a virtual network into several adjacent star configurations and reduces the size of large-scale virtual network evidently. At the same time ， a resource allocation model matching nodes and their adjacency links is proposed ， which enables nodes mapping to adapt links ’ resource state and makes links mapping match with the resource size of related nodes in a coordinated way. Thus ， the inharmonious operation of mapping nodes and links ， as well as the mismatching of allocating network resources ， is solved effectively.Simulated results show that the proposed algorithm reduces the mapping path length of virtual links and improves the mapping efficiency of virtual networks as well as the load-balancing performance ， and thus high acceptance ratio of virtual network requests can be achieved.