Trainee Project
Wireless communicating objects energy optimization by using a digital twin of the network
2022/02/01 - 2022/05/30
During the last twenty years, the energy optimization of wireless mesh networks (WSN, IoT) has become a major issue. Classical methods for managing this type of network are based on a self-organization approach of the nodes to optimize its energy consumption while guaranteeing the collection requirements. The decision making, then distributed and partial, most often leads to local optima [Delgado 2014]. The use of a digital twin of the network (or DT), by having the total vision of the network, allows centralizing the decision and hoping for a more time-efficient global optimal solution [Occello&al. 2019]. In addition to providing a global observer of the network, a DT allows integrating changes in application requirements ("data plane", in the sense of the SDN paradigm) and thus developing a scalable collection strategy ("control plane", in the SDN sense) [Nguyen&al. 2016].

In his PhD thesis, [Wan, 2021] proposes a model for evaluating the energy consumption of a network of communicating objects collecting data cyclically and a multi-agent architecture for observing the evolution of the energy state of nodes. This approach has been proven for a linear communicating structure [Wan & al., 2020]. A generic model, allowing to evaluate the energy consumed for any type of structure and to discretize data aggregation functions on all or part of the network nodes, has been implemented in a multi-agent simulator. This model relies on 3 types of inputs:
- the data routing structure (or network communication graph) that defines the path taken to bring the data up to a gateway;
- the internal processing (in-network processing) that can be performed by all or some of the nodes on the collected data;
- the communication technology used by the network, which is translated into parameters allowing to quantify the activity of each object.

The main objective of this master is to define the management of the data collection based on a digital twin using the H.Wan model, and to show the interest and/or the complementarity with respect to the more traditional distributed approaches of network self-organization. It will be considered to use the energy consumption as a criterion to evaluate different collection alternatives, obtained by combinations of different structures and internal treatments. This work will be used, in the longer term, for the development of a closed loop (re)configuration mechanism.
This demonstration could be implemented by simulation and comparison of the energy consumption of different approaches in the literature. It will also be used to complete the digital twin prototype associated with the McBIM platform.
Sustainability, Wireless networks, Digital Twin, Software Defined Network
Master Internship
Duration: about 5 months

Location: CRAN (ISET Department), Faculty of Science, Vandoeuvre-Lès-Nancy

Remuneration: according to statutory amounts

Expected Profile:
- Master's degree or with "network or IT" colouring
- Development and/or simulation skills

Transmission of the application form (CV, M1 notes, reference, ...) by e-mail to and
Eco-Technic systems engineering