Abstract
The Automated Network Games Enhancement Layer (ANGEL) project aims to leverage Machine Learning (ML) techniques to automate the classification and isolation of interactive (e.g. games, voice over IP) and non-interactive (e.g. web) traffic. This information is then used to dynamically reconfigure the network to improve the Quality of Service provided to the current interactive traffic flows and subsequently deliver improved performance to the end users. Within this scope, the project will develop protocols that allow the adjustment of Consumer Premises Equipment (CPE - eg. cable/ADSL) configuration to provide better quality of service to interactive flows detected in real-time.
This document provides the motivation and describes typical use cases for the ANGEL architecture. It also defines the basic building blocks of the architecture and specifies the requirements for them.