Automated Deployment of Serverless Functions
Common approaches for “Serverless Computing” (i.e. script/function code execution in virtual environment triggered by events) usually work in centralized deployments (e.g., Amazon AWS Lambda, Microsoft Azure Functions, Google Cloud Functions, IBM Cloud Functions / Apache OpenWhisk).
In contrast, Distributed Serverless Computing (DSC) is based on the principle that function execution happens in distributed datacenters, where code can be instantiated in machines located in different physical places (adding a network aspect).
The project aims to achieve:
- An orchestration software to decide the placement of micro-functions into heterogeneous hardware platforms and the routing of related dataflows in order to support distributed serverless computing considering user mobility, traffic dynamics, and application requirements
- An application for the ONOS (Open Network Operating System) controller that combines, consolidates and deploys multiple micro-NFs in the network and enforces data flow routing, thus enabling DSC
Used tools: linux, onos, docker
Programming language: python
Analysis of field measurements in telecommunications operator network
We have a large amount of data collected during field operations at a large Italian network operator. The candidate will set-up an automated procedure for information extraction for network measurements and identification of suitable performance indicators and alarms.
Used tools: data science/data analysis libraries
Programming language: python
Artificial Intelligence in the Air
Allocation of hard network slices over the 5G and the future 6G interfaces is a complex task, which requires to find a trade-off among multiple objectives with limited information and limited time to find a solution. New approaches based on Artificial Intelligence are emerging to address this problem.
The candidate will study the available options and design a suitable algorithm.
Used tools: machine learning libraries
Programming language: python, matlab