The ABCD project proposes a dynamic evaluation of the users’ mobility and content consumption that can be then leveraged for a proactive engineering of the Cloud instances close to the identified access points. Specifically, we envision: (i) a distributed behavioral classification method for predicting jointly user macro-mobility and usages with an acceptable accuracy, (ii) a method to estimate the volume of users per access point over time, their behavioral typology and their usage typology (accessed services), (iii) the definition of mobile Cloud networking protocols jointly managing user and machine mobility to transparently migrate virtual machines to the places where users are. These procedures are not currently deployed in access networks, but the current trend and technology context suggests that it is just a matter of time. It is therefore of paramount importance to position our research effort in this direction to contribute to present advances in technologies.
Outcome of the project could enhance the current understanding of access network user mobility, create patents as well as synergies with the EIT KIC ICT-Labs and the FP7 IRSES MobileCloud project.