# Results and Achievements of the ALLIANCE Project: New Network Solutions for 5G and Beyond
## 6 The SDN/NFV Domain
### Control/Management/Orchestration Architecture  
In ALLIANCE, a complete SDN/NFV-based control/management/orchestration architecture has been designed to deliver network slices customised to the requirements of the vertical services and applications [75; 76; 77]. The major challenge in this regard is that the provisioning of network slices may affect multiple SDN-controlled segments/technologies (optical access networks, metro, core and DCs). Moreover, special attention must be dedicated to the quality maintenance of the slices during their runtime. Since slices are employed to support several services on top, it becomes essential to monitor selected Key Performance Indicators (KPIs) of the slices to identify situations in which the current quality of services could be compromised. This way, the maintenance of slice QoS as well as the quality experienced by the user (i.e., QoE) can be achieved.  
The proposed architecture has been inspired by the approach known as the MAPE cycle (Monitoring, Analysis, Planning and Execution): the four steps of this approach allow the automatic and autonomous management of the optical networks and the DCs resources. The first step (monitoring) is based on the collection of the different metrics that can be collected through sensors. The second step (analysis) consists of the analysis of the data collected to determine the need for actions to maintain the quality of the supported slices/services. Taking into account the enormous volume of data collected, the application of ML techniques can detect in advance possible failures in the infrastructure. The third step (planning) is required in the case of detecting the need for reconfiguration of the network to continue providing the service with the same quality. In particular, it refers to defining the actions to be enforced, thus determining the fourth step (execution) that represents the implementation of the defined reconfigurations.  
In the context of the application of the MAPE approach for the maintenance of quality of the deployed network slices, end-to-end QoS-based monitoring tools have been designed and implemented. The designed architecture also enables reception of a direct QoE input that can provide valuable information on the service state as perceived by the user/vertical. In particular, a Mean Opinion Score (MOS) value is constantly collected. In our approach, both types of parameters (Qos and QoE) are constantly monitored, and upon a negative user feedback, a new architectural component, i.e., the QoE optimiser, has been introduced, being in charge of maintaining awareness of the user QoE to guarantee the correct service operation.  
We have experimentally assessed the overall architecture using a three-segment network scenario, based on the interconnection between (cloud and/or edge) DCs through wide-area networks [75]. In particular, each network segment is connected to its Open-DayLight (ODL)-based SDN controller, while each DC is managed by a single OpenStack entity. Each DC hosts a single virtual machine and network connectivity is delivered across the three network segments. The QoS metric for the deployed slice is the packet  
Figure 6: Experimental data from [74] for probabilistically shaped M-QAM signals. Symbols correspond to measured points. Dashed lines correspond to a linear interpolationloss ratio (PLR) experimented by the data flows across the Virtual Network Functions (VNFs). Hence, we have implemented a policy stating that as a result of a PLR greater than a pre-defined threshold, the configured slice network bandwidth must be increased to suitable levels. In particular, we have validated that once the PLR reaches the threshold, the policy is activated increasing the bandwidth of the provisioned network resources and successfully dropping PLR to a negligible value. In summary, we have proved that the proposed architecture can maintain the desired QoS levels over the time under dynamic conditions that may affect the quality of the delivered services.