Date : April 16, 2020, 1 p.m. - Room :Visio-conférence

Self-stabilization and Highly Dynamic Networks

Anais DURAND - MC LIMOS, Université Clermont Auvergne

Mobile networks, robot fleets, swarms of drones are example of highly dynamic networks, i.e., networks whose topology changes overtime. In these networks, topological changes cannot simply be considered as a perturbation but are truly inherent to the system. However, fault-tolerant distributed computing researches mainly focused on networks whose topology is static or systems where topological changes are rare and sparse.

Self-stabilizing systems are able to recover a correct behavior in finite time and without any external intervention, after some perturbations (e.g., memory corruption, message losses) put the system in an arbitrary state. Self-stabilization is a very promising solution to withstand faults in highly dynamic networks.

I will present some ongoing work aiming to explore the power of self-stabilization in highly dynamic networks (what problems can we solve? what hypotheses on the dynamic of the system are necessary?, etc.). We consider Time-Varying Graphs to model the dynamic of the network topology.