In cloud computing environment, service provider (SP) can pay for the resources from infrastructure provider (InP) on-demand to deploy their services. In the case, SP can focus on service business without considering their physical infrastructures and expertise of maintenance. Only providing resources in term of virtual machines, the traditional InPs do not ensure network performance and bandwidth isolation. As the network virtualization is developed, especially the SDN concept, some researchers advocate InPs to provide resources in term of virtual data center (VDC) to solve these limits. Despite many advantages of VDC, there is also a new challenge that is the VDC embedding problem known as an NP-hard problem. With the goal of minimal cost and maximal revenue, it solves the problem of allocating resources to fulfill the SPs’ requirements. Considering the tradeoff of VDC reliability and embedding cost, a VDC embedding algorithm based on topological potential and modularity is proposed to improve acceptance ratio and the InPs’ revenue. Moreover, we further optimize the algorithm based on a given threshold by selecting high RevenueCost ratio VDCs. Extensive simulations show that compared with the existing algorithms, our approach is capable of reducing the core bandwidth consumption in data center. Furthermore, these proposals can accept more VDCs and obtain more revenue.