Distributed AI for Mobile Ad Hoc Clouds

The unprecedented expansion of Cloud Computing, Internet of things and the recent advances in AI and Big Data analytics techniques are opening the door for new breeds of intelligent services and applications. However, such services and applications require a large computing capacity. Unfortunately, in dynamic environments, characterized by highly mobile devices and intermittent connectivity, it becomes challenging to run such services and applications with a guaranteed performance, especially when it is not possible to rely on any fixed infrastructure giving access to cloud platforms with powerful servers. This project aims at addressing this challenge by designing novel architectures and management mechanisms for Mobile Ad hoc Cloud (MAdoC), a dynamic cloud made of interconnected IoT devices with no dependence on a fixed infrastructure. A high-performance and resilient software-defined heterogeneous MAdoC will be proposed, it leverages recent technological advances in Software-Defined Networking (SDN), Big Data analytics, and Machine-Learning techniques.

Intern: 
Jitender Grover;Mohamed Ibrahim Mahmoud Mohamed El Emary
Superviseur universitaire: 
Diala Naboulsi;Mohamed Faten Zhani;Georges Kaddoum;Muthucumaru Maheswaran
Province: 
Quebec
Secteur: 
Partner University: 
Discipline: 
Programme: