Dynamic Resource Scaling using vNetRunner and MicroOpt

Background Reading

For a brief overview of dynamic resource scaling, please see intro-to-drs.

5G Dynamic Resource Scaling

We will be conducting our hands-on sessions in room MC2061, which is equipped with workstations to facilitate the workshop. Once we have access to the workstations, we will be using JupyterLab for our exercises. Once you have accessed your workstation, please proceed to the following link to get started: 5GDynamicResourceAllocation

Conclusion and Next Steps

Congratulations! By completing the three notebooks, you should now have a solid understanding of how the dataset gathered from 5G network can be used for network modeling and for 5G slice management and orchestration.

Key Takeaways:

• AI-based approaches can be effectively used for autonomous 5G network management and orchestration.
• You have learned how to train individual VNF models and compose them to form end-to-end slice model.
• You have learned how to leverage the network model and use primal-dual optimization to perform dynamic resource scaling for network slices.