## 4 Toward Cognitive Connectivity: The Case of Dynamic Bandwidth Management
### On the Integration of the Bandwidth Management into the COGNIFOG Stack  
The conducted PoC exemplifies how network management techniques can effectively combat BW starvation and contention issues caused by resource-intensive services on a  
Figure 4: The K3s cluster designed for the PoC. The red bullet indicates the activation of the egress BW limitation only at the final stage of the performance evaluation. Figure 5: Resulting throughput of TCP high-priority and UDP low-priority traffic. shared network link. In this case, the BW limitation technique was manually implemented, but the final version of the COGNIFOG framework shall integrate it with advanced monitoring, orchestration, and AI modules to achieve true cognitive connectivity that automatically adapts services to dynamic network conditions. This section elaborates on how the COGNIFOG framework could integrate the BW management feature, which is just one of the multiple functionalities encompassed under the flexible and dynamic provisioning and management of computing, storage, and networking resources. To illustrate this, a high-level interaction flow diagram of the main elements of the COGNIFOG stack is provided in Figure 6.  
Assuming proper deployment and interconnection of the depicted COGNIFOG elements, their interactions can be grouped into four main stages:  
1. **Modeling:** After the user authentication, application image(s) are uploaded to an image repository. SLA policies and the application description model (consisting of manifest files, plugins, and specific requirements) are also defined by the user in the front-end dashboard. 2. **Deployment:** The requirements of the application description model, along with the SLA policies, are received by the smart allocator. With these inputs, it is able to design an initial application deployment model, which is then communicated to the orchestrator manager and the user via the front-end dashboard. Subsequently, slices containing computing, network, and access network chunks are created under a _deployment-driven_ model on the resources of the working cluster [50]. Finally, the application is deployed on the targeted nodes according to the application description model. 3. **Operation:** During operation, the end user receives not only application data but also updated information on the status of the deployment itself. For its part, the smart allocator also receives information on the status of the slices, performance metrics, and SLA compliance, which feeds its intelligent engine and may trigger a deployment reconfiguration if necessary. 4. **Goverance:** The depicted interaction flow shows how a new application deployment model is designed by the smart allocator. This process may be initiated after detecting non-compliance with SLA policies. As in the initial deployment, the model is commu  
Figure 6: High-level interaction flow diagram of the COGNIFOG stack. nicated to the orchestrator manager and the user via the front-end dashboard. The slices and the application are then redeployed according to the new model to enhance overall system efficiency and performance. Returning to the specific case of the BW management functionality, the final version of the COGNIFOG stack shall automate most of the processes described in the PoC. For instance, during the modeling stage, a user could define an SLA policy for TCP high-priority traffic to ensure a specific value of \(S_{\text{TCP}}\). Then, in the operation stage, if the smart allocator detects that the value of \(S_{\text{TCP}}\) reported by the performance metrics of the monitoring system does not meet the SLA policy, it would automatically initiate the reconfiguration of the deployment as part of the governance stage. Based on the information of the infrastructure (i.e., available resources and status) and considering the compliance with the SLA policy, the smart allocator shall decide to limit the available BW for the UDP traffic corresponding to low-priority services without further human intervention.