To minimize the cost of the VNF deployment in an NFV datacenter environment with Optical Network interconnection [7; 8; 9], an integer linear programming model was first established, and then three heuristic algorithms were proposed to solve the integer linear programming model effectively [10]. To minimize the total cost of the energy consumption and the revenue loss due to QoS degradation, an efficient algorithm, which is based on the back-to-back strategy, was designed [11]. To solve service chain and resource allocation problem, a mixed-integer linear programming model was proposed [5], and a heuristic-based algorithm, which consists of two sub-algorithms: one-hop optimal traffic scheduling algorithm and VNF chain composition algorithm, was proposed. [PERSON] et al. [12] formulated the VNF deployment problem as an integer linear programming model and proposed a simulated annealing based heuristic to get approximate solutions in shorter time. [PERSON] et al. [13] proposed an algorithm based on eigenvalue decomposition for the VNF deployment in EON (Elastic Optical Network) for the sake of satisfying user requirements and maximizing provider revenue. To lower the costs, reconfiguration of cloud and bandwidth resources is needed. Reconfigurations algorithms [14] have been proposed that move the execution of the VMs so as to guarantee the use of lower cost datacenters. Though the reconfiguration policies allows for lower costs, they involve reconfiguration costs that have been investigated in [14]. In the case of optical interconnection of the NFV sites, the high optical switch reconfiguration time leads to limit the number of switch reconfigurations to guarantee high switch throughput [15]; for instance, the circuit reconfiguration time of a Micro-ElectroMechanical Systems (MEMS) based optical crossconnect is in the order of 1 s [15] that leads to no more than one reconfiguration every 10 s to reach 90% switch throughput. The objective of the paper is to evaluate the advantages that the NFV technology with optical interconnection allows us to achieve in terms of cloud and bandwidth resource cost saving under the constraint on the maximum number of switch reconfigurations. We have provided an Integer Linear Programming (ILP) formulation of the optimization problem. It was inherited from the one proposed in [16] with the addition of a constraint on the maximum number of switch reconfigurations. Because of the computational complexity of the defined ILP, we propose a low computational complexity heuristic that allow us to study very complex network scenarios. The heuristic is based on the application of a constrained shortest path algorithm proposed in literature and referred to as Label Setting [17; 18]; it consists of the evaluation of a shortest path in a graph in which each edge is labeled with two labels; the shortest paths are evaluated on the basis of the values of the first labels while the second label allows us to take into account the constraint on the maximum number of switch reconfigurations. The paper is organized in five Sections. The related work is reported in Section 2. The reference scenario is described in Section 3. An efficient heuristic is illustrated in Section 4. The results of the heuristic and the optimization ones are compared in Section 5 in the case of a small size network. The impact of the maximum number of switch reconfigurations on the cost saving is also evaluated in Section 5 in the case of large networks. Conclusions and future research items are discussed in Section 6. Appendix A provides an Integer Linear Programming (ILP) formulation of the cloud and bandwidth resource allocation problem when the number of switch reconfigurations is limited. Appendix B provides a formal description of the proposed heuristic.