Trainee Project
Title:
Efficient and sober control strategies for IoT architectures
Dates:
2023/03/01 - 2023/07/31
Supervisor(s): 
Lemia LOUAIL , Jean-Philippe GEORGES
Description:
In recent years, the environmental and social footprint of digital communication networks has emerged as a major issue in the deployment of

communication infrastructures. This aspect should not be reduced to the sole minimization of a local energy consumption for a single communication, but

on the contrary to the whole infrastructure and to other metrics including the different sources of pollution (e.g., the carbon cost per bit taking into account

the mode of production of the energy used or the radio-frequency pollution).







Moreover, the networks of the future (especially 5/6G), the pillars of digital ubiquity, must be able to reconfigure themselves automatically, whether to

support a new management strategy in the context of the industry of the future or the provision of specific services during a temporary event such as a

sporting event. This is even more the case in industrial and wireless Internet of Things environments, where the dynamics of traffic, mobility, QoS

requirements (such as range or bandwidth) and environment are great.







In this context, it becomes necessary to implement network control architectures that must optimize a budget shared by the whole network, concatenating

both pollution and QoS metrics.







The objective of this topic is to study the different reconfiguration strategies of an IoT architecture in order to reduce its environmental footprint. The goal is

to study the state of the art of network control solutions in IoT and those integrating both QoS and Environmental Integration Quality metrics.
Department(s): 
Modeling and Control of Industrial Systems