FOSSATI Francesca

PhD graduated
Team : Phare
Departure date : 02/29/2020

Supervision : Stefano SECCI

Novel notions of fairness and resource allocation for congested networked systems

Fairness is topic that emerges in many fields and that is linked to the resource allocation and fair division problems. In networking and computing the legacy approach to solve these situations is to model them as a single-decision maker problem using classical resource allocation protocols as the proportional rule or the max-min fair allocation.
The evolution of the telecommunication network technologies and advances in computing power and software design allow an increasing degree of freedom and programmability to resource allocation and routing decision-making logics. Furthermore, software-defined radio and virtualized network platforms are used on top of a shared infrastructure making possible a real-time auditability of the system by its tenants and users. Therefore, novel networking contexts such that tenants can be aware of other users’ demands and the available amount of the resource or they can have a partial information on the system has to be considered. Together with new type of decision-making modeling for 5G systems, it is necessary to move from single-resource allocation to multi-resource allocation. In fact, with the introduction of the network slicing concept, we need logically-isolated network partitions that combine network, computation and storage programmable resources.
In this thesis we aim to provide a theoretical and formal analysis and redefinition of fairness of resource allocation for congested networked system, i.e., in the challenging situation in which resources are limited and not enough to fully satisfy users’ demand. We analyze, propose and evaluate numerically centralized, decentralized, single and multi-resource allocation rules.

Defence : 11/29/2019

Jury members :

David COUDERT, INRIA Sophia Antipolis [Rapporteur]
Joaquin Sanchez Soriano, Miguel Hernandez ,University of Elche [Rapporteur]
André-Luc BEYLOT, ENSEITH Toulouse
Nancy PERROT , Orange Labs
Patrice PERNY , Sorbonne Université
Stefano MORETTI, , Université Paris Dauphine
Stefano SECCI, CNAM Paris

Associate Professor

2017-2023 Publications