Abstract-In the currently dominant cloud computing paradigm, applications are being served in data centers (DCs) which are connected to high capacity optical networks. For cost efficiency reasons, in both DC and optical network domains, virtualization of the physical hardware is exploited. In a DC, it means that multiple so-called virtual machines (VMs) are being hosted on the same physical server. Similarly, the network is partitioned into separate virtual networks, thus providing isolation between distinct virtual network operators (VNOs). Thus, the problem of virtual network mapping arises: how to decide which physical resources to allocate for a particular virtual network? In this paper, we study that problem in the context of cloud computing with multiple DC sites. This introduces additional flexibility, due to the anycast routing principle: we have the freedom to decide at what particular DC location to serve a particular application. We can exploit this choice to minimize the required resources when solving the virtual network mapping problem. This paper builds on our earlier work and solves the resilient virtual network mapping problem that optimally decides on the mapping of both network and data center resources, considering timevarying traffic conditions and protecting against possible failures of both network and DC resources. Previously, we developed a model to solve the multi-period traffic case one step at a time: given the virtual network mapping in period t, we determine the (possibly changed) mapping for t + 1. Compared to that previous work, we now (i) define a truly multi-period model path formulation exploiting column generation, and (ii) demonstrate its scalability on a nation-wide network with traffic that varies across multiple periods.