Duration: 1 year
Starting Date: September 1, 2021
Keywords: 5G networks, Resource Allocation, Optimization, Network Slicing
5G is envisioned to be a multi-service network supporting a wide range of verticals with a diverse set of performance and service requirements. For example, the ITU and 5G-PPP have identified three general use case families: enhanced mobile broadband, massive machine-type communications, and critical communications. In fact, these applications and services impose very heterogeneous and diverse requirements that future mobile networks will have to meet, in terms of latency, throughput and reliability. The stark differences between these use cases translate to a set of heterogeneous requirements that cannot be satisfied by a one-size-fits-all architecture. Slicing a single physical network into multiple isolated logical networks has emerged as a key to realizing this vision.
Network Slicing is one of the key elements in future 5G mobile networks, as it allows the mobile infrastructure to be divided into virtual networks, called network slices. Using virtualization technologies, network slicing allows building isolated logical networks, on a per-service basis, on top of a single physical network. The network slices could be rented periodically and dynamically by different entities (i.e., vertical industries, mobile virtual network operators MVNO, etc.) and can thus be adapted to support new services that will emerge in the 5th generation of mobile networks and beyond [1-2]. However, an essential underlying problem in Network Slicing is the efficient sharing of mobile network resources. In this context, solutions based on centralized algorithms have recently been proposed in the literature [3-6]. These algorithms consider that telco operators have complete knowledge of each vertical industry’s system parameters and preferences (« tenant ») such as the capacity, number, and location of the elements of the served infrastructure. Thus, telecom operators seek to maximize their profit and use their resources but at the expense of individual customers.
However, in realistic scenarios, vertical industries and MVNOs may be reluctant to disclose sensitive information to the telecom operator. At the same time, centralized approaches do not consider the competitive and selfish behaviour of modern vertical industries that will dynamically adopt different strategies to maximize their utility without considering the broader needs of the network as a whole. For all these reasons and complexity reasons of centralized algorithms, the use of distributed algorithms for network slicing will be favoured because, in practice, these algorithms are more likely to be adopted by vertical industries. This project aims to propose distributed algorithms for Network Slicing by comparing different approaches using optimization and machine learning.
The goal of this postdoc is to study the performance of distributed algorithms for mobile network resource sharing. These algorithms will be evaluated in terms of efficiency (price of anarchy) compared to centralized approaches as well as in terms of fairness distribution of resources. In this context, a new notion of fairness should be introduced in order to consider the different resources and the distribution of allocations for each resource (bandwidth, power, memory, etc.).
This project will make use of several mathematical tools such as: discrete optimization, machine learning, game theory, graph theory as well as other protocols of distributed systems.
The Post-doc will be involved in the following tasks:
• Bibliography on 5G networks, resource allocation, network slicing
• Development of innovative distributed algorithms, modeling and evaluation.
• Performance evaluation using simulations (NS-3 or MATLAB)
The applicant, having PhD degree (acquired in telecommunication engineering or computer science),
should have good skills in networks protocols, modeling methods, simulation, optimization approaches
and C/C++, Python or MATLAB programming.
To apply, please provide:
• a cover letter detailing your suitability for the position in question
• a detailed CV including the list of publications
• the name and address of one or two referees
Laboratoire des Signaux et Systèmes (L2S), UMR 8506 (CentraleSupélec, Université Paris Saclay et
• Sahar Hoteit, Associate Professor e-mail: email@example.com, phone: +33 1 69 85 17
 NGMN Alliance, « Description of Network Slicing Concept », 2015.
 I. Afolabi, T. Taleb, K. Samdanis, A. Ksentini and H. Flinck, “Network Slicing and Softwarization: A
Survey on Principles, Enabling Technologies, and Solutions” IEEE Commun. Surveys Tuts., Vol. 20, pp.
 M. Vincenzi, A. Antonopoulos, E. Kartsakli, J. Vardakas, L. Alonso and C. Verikoukis, “Multi-tenant
slicing for spectrum management on the road to 5G”. IEEE Wireless Comm., vol. 24, pp. 118-125.
 S. D’oro, F. Restuccia, T. Melodia and S. Palazzo, “Low-complexity distributed radio access network
slicing: Algorithms and experimental results”, IEEE/ACM Trans. on Networking, Vol. 26, p. 2815-2828.
 Quang-Trung Luu, Michel Kieffer, Alexandre Mouradian, Sylvaine Kerboeuf, “Aggregated Resource
Provisioning for Network Slices”, IEEE Global Communications Conference GLOBECOM, 2018.
 Francesca Fossati, Stefano Moretti, Patrice Perny, Stefano Secci. Multi-Resource Allocation for
Network Slicing. IEEE/ACM Transactions on Networking, IEEE/ACM, 2020, Vol. 28, pp.1311-1324.