###### Abstract
However, its use in conjunction in the network can enable the reduction of latency, cost and energy consumption. This is done by using virtualized BBUs, i.e., virtual functions running on multicommodity servers (i.e., those from MEC) implementing the functionality of a BBU [3]. Examples of architectures addressing that idea are the Heterogeneous Cloud Radio Access Network (H-CRAN) [11], which combines C-RAN with cloud computation techniques deployed at some nodes of the network, or the Cloud/Fog RAN architecture [12], which places Local Processing Units at the network cells to deploy cloud services and, therefore, virtual BBU (vBBU) functions, closer to the end user. Network Function Virtualization (NFV) and Software Defined Networking (SDN) are also facilitating the realization of 5G by changing the manner in which operators deploy their end-user services. Nowadays, operators offer services like video streaming, web browsing, data transmission or voice services by executing specific tasks, known as network functions. Modern networks deploy network functions on dedicated hardware or middleboxes. Since middleboxes are costly and inflexible, operators incur an increase in capital and operational expenditures any time they deploy new and complex services. NFV is a technology that deploys network functions as software appliances called Virtual Network Functions (VNFs). VNFs are instantiated in Commercial-Off-The-Shelf (COTS) servers, which can host multiple instances of different VNFs, thus facilitating the deployment of complex network services and the efficient dimensioning of the network. Moreover, COTS hardware can be placed at data centers, Central Offices (CO) [13], but also optical network edge nodes can be NFV-enabled nodes thanks to the MEC approach. Consequently, NFV facilitates the deployment of new network services avoiding a rise in the network cost. The traffic associated to each service must traverse a Service Chain (SC), i.e., a set of VNFs concatenated in a specific order while satisfying latency, and bandwidth requirements, as well as computing resources and the maximum number of concurrent users per VNF requirements. Therefore, deciding where to host VNFs and which particular instances should be concatenated to set up SCs while satisfying the aforementioned requirements are some of the problems that operators face when implementing NFV. We refer to this problem as the VNF-Provisioning problem. Lastly, operators must decide whether to perform the VNF-Provisioning at peak loads, which may cause an inefficient use of resources, or take advantage of the benefits of NFV and SDN and perform periodic network re-plannings to adapt the resources to the actual traffic. In this paper, we address the NFV-based network dimensioning problem in a 5G network to deploy services like Video Streaming, VoIP or Web browsing. To achieve this objective, we consider the implementation of Heterogeneous Cloud Radio Access Network (H-CRAN) in the network using traditional C-RAN technology (i.e., without splitting BBUs into DUs and CUs) and including MEC servers at the first aggregation site, i.e., at the Access Office (AO) serving each cell of the network, in order to deploy both VNF and vBBUs functions. We assume that RRHs connect to the virtualized BBUs deployed at the AO using optical communications, in a similar manner as [6; 12]. We extend the Fog/Cloud RAN architecture in Reference [12] to benefit from the advantages of the MEC paradigm. Therefore, the AO also hosts a MEC server to deploy the virtual BBUs and other possible VNFs. We use optical technologies to connect the AO to the CO, equipped with IT resources and assume that the VNFs required to deploy the selected services can be deployed either on the MEC server at the AO or on the CO.  
Firstly, we propose a genetic algorithm to solve the VNF-Provisioning problem.