# Advances in Improving Energy Efficiency of Fiber-Wireless Access Networks: A Comprehensive Overview
## 5 Energy Efficiency Analyses of FiWi Networks Based on Multi-Access Edge Computing  
The MEC concept introduces the cloud computing processes into FiWi networks, which are closer to mobile end UDs, more specifically at the mobile network edge. By exploiting an approach based on processing part of the user traffic in the cloud servers located at the edge of the mobile network, the transmission delay in the network is reduced and central servers at the cloud are less loaded. Figure 10 shows the generic network architecture that encompasses MEC and a centralized cloud paradigm over the FiWi access network. Such a network is referred to as a cloud-MEC FiWi broadband access network (CM-FiWi). The architecture presented in Figure 10 consists of a long-reach optical backbone network connected to a centralized cloud and a standard FiWi access network supporting different wireless access technologies such as LTE, 5G or WLAN. One or more MEC servers are connected near the UDs of the fixed-access network or integrated with the ONU with the AP (ONU-AP) node or the ONU with base station (ONU-BS) node via a direct optical connection (Figure 10). This connection enables cloud services at the edge of the network, which can comprise the access of some wireless local/personal networks or cellular mobile networks (Figure 10). In such a FiWi network based on the MEC concept, ONU devices can also retain their traditional role, i.e., provide fixed services to users via the fiber-to-the-x (FTTx) concept (Figure 10). This technology and architecture are key to the evolution towards full installation of the 5G networks and especially 6G networks, since it enables the transformation of mobile networks towards a programmable platform that meets the mobile cellular network requirements for increased bandwidth, lower delay and better scalability and configurability [96]. As one of the key technologies for enabling the full potential of 5G networks [97], MEC creates a pathway for the practical implementation of applications that require extremely low latencies with high reliability. Some examples of such applications include tactile internet, augmented reality/virtual reality, connected cars and mission-critical IoT systems. Moreover, the FiWi networks based on the MEC concept can reduce the overall operator CAPEX and OPEX through the exploitation of the existing infrastructure and through the implementation of integrated resource-management mechanisms. The authors in ref. [9] reviewed the challenges and possible design scenarios for implementation of MEC-enabled hybrid FiWi networks with various RAN technologies  
Figure 10: The generic architecture of a CM-FiWi access network. (WLAN, 4G, LTE-A and HetNets) (Table 4). Additionally, using the TDMA scheduling resource-management scheme, the Ethernet-based FiWi network was further inspected regarding delay performance, battery life of edge UDs and response-time efficiency. The results showed that the MEC over FiWi can significantly reduce power consumption and extend the battery life of edge UDs (Figure 10). Furthermore, the same group of authors proposed, in ref. [91], a cloudlet-aware resource-management scheme that decreases the delay of offloading tasks and extends the battery life of edge UDs (Table 4). This scheme incorporates offloading the FiWi dynamic bandwidth allocation process and was designed using two TDMA layers to improve network performance. Analysis showed that the proposed solution, which incorporates cloudlets into the MEC FiWi networks, could lead to a significant reduction in energy usage for edge UDs and extend their battery life by several hours. The proposed architecture and resource-management strategy could be a useful solution for the implementation of MEC in future technologies such as the 5G tactile internet. For the computational offloading scheme that involves moving intensive computing tasks to a cloud located at the edge of the mobile network is shown to be beneficial in improving EE and reducing latency for UDs in the mobile network [92]. Hence, the authors in ref.