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.

One PhD student (Supervision / Co-supervision)

2017-2023 Publications

• 2023
  • M. Sharara, F. Fossati, S. Hoteit, V. Vèque, F. Bassi : “Minimizing energy consumption by joint radio and computing resource allocation in Cloud-RAN”, Computer Networks, vol. 234, pp. 109870, (Elsevier) (2023)
• 2022
  • L. De Lara, F. Fossati, S. Rovedakis : “Robust Multi-Resource Allocation Against Controller Failures in Network Slice Provisioning”, 2022 IEEE 11^th International Conference on Cloud Networking (CloudNet), Paris, France, pp. 28-33, (IEEE), (ISBN: 978-1-6654-8627-9) (2022)
  • F. Fossati, S. Rovedakis, S. Secci : “Distributed algorithms for multi-resource allocation”, IEEE Transactions on Parallel and Distributed Systems, vol. 33 (10), pp. 2524-2539, (Institute of Electrical and Electronics Engineers) (2022)
• 2020
  • F. Fossati, S. Moretti, P. Perny, S. Secci : “Multi-Resource Allocation for Network Slicing”, IEEE/ACM Transactions on Networking, vol. 28 (3), pp. 1311-1324, (IEEE/ACM) (2020)
  • F. Fossati, S. Moretti, S. Rovedakis, S. Secci : “Decentralization of 5G slice resource allocation”, IEEE/IFIP Network Operations and Management Symposium (NOMS), Budapest, Hungary (2020)
• 2019
  • F. Fossati : “Novel notions of fairness and resource allocation for congested networked systems”, thesis, phd defence 11/29/2019, supervision Secci, Stefano (2019)
  • F. Fossati, D. Medhi, S. Moretti, S. Secci : “Error Estimate and Fairness in Resource Allocation with Inaccurate Information Sharing”, IEEE Networking Letters, vol. 1 (4), pp. 173-177, (IEEE Communications Society) (2019)
  • F. Fossati, S. Moretti, S. Secci : “Multi-Resource Allocation for Network Slicing under Service Level Agreements”, 2019 10^th International Conference on Networks of the Future (NoF), Rome, Italy, pp. 48-53, (IEEE) (2019)
• 2018
  • F. Fossati, S. Hoteit, S. Moretti, S. Secci : “Fair Resource Allocation in Systems with Complete Information Sharing”, IEEE/ACM Transactions on Networking, vol. 26 (6), pp. 2801-2814, (IEEE/ACM) (2018)
• 2017
  • F. Fossati, S. Moretti, S. Secci : “A Mood Value for Fair Resource Allocations”, IFIP Networking 2017, Stockholm, Sweden, (IEEE) (2017)