Dimensionnement et optimisation des réseaux de collecte sans fil

The main work of this thesis focuses on the wireless backhaul networks. We studied different optimization problems in such networks that represent real challenges for industrial sector.The first issue addressed focuses on the capacity allocation on the links at minimum cost. It was solved by a linear programming approach with column generation. Our method solves the problems on large size networks. We then studied the problem of network infrastructure sharing between virtual operators. The objective is to maximize the revenue of the operator of the physical infrastructure while satisfying the quality of service constraints of virtual operators customers of the network. In this context, we proposed a robust model using mixed integer linear programming. In the following problem, we proposed a robust energy-aware routing solution for the network operators to reduce their energy consumption. Our solution was formulated using a mixed integer linear program. We also proposed heuristics to find efficient solutions for large networks. The last work of this thesis focuses on cognitive radio networks and more specifi- cally on the problem of bandwidth sharing. We formalized it using a linear program with a different approach to robust optimization. We based our solution on the 2-stage linear robust method.L’essentiel des travaux de cette thèse porte sur les réseaux de collectes de données sans fil. Nous avons étudié différents problèmes d’optimisation dans ces réseaux qui représentent de vrais challenges pour les industriels du secteur. Le premier problème porte sur l’allocation de capacités sur les liens à coût minimum. Il a été résolu par une approche de programmation linéaire avec génération de colonnes. Notre modèle permet de résoudre des problèmes de grandes tailles. Nous avons ensuite étudié le problème du partage d’infrastructure réseau entre opérateurs virtuels avec comme objectif de maximiser les revenus de l’opérateur de l’infrastructure physique tout en satisfaisant les demandes et les contraintes de qualité de service des opérateurs virtuels clients du réseau. Dans ce contexte, nous avons proposé une formulation robuste du problème en programmation linéaire en nombres entiers mixte. Un autre point de dépenses dans ce type de réseau est la consommation d’énergie. Nous avons proposé une solution robuste, de routage basée sur la consommation d’énergie du réseau. Notre solution a été formulée en utilisant un programme linéaire en nombre entiers mixte. Nous avons aussi proposé des heuristiques afin de trouver assez rapidement des solutions pour de grandes instances. Le dernier travail de cette thèse porte sur les réseaux radio cognitifs et plus précisément sur le problème de partage de bande passante. Nous l’avons formalisé en utilisant un programme linéaire mais avec une autre approche d’optimisation robuste. Nous utilisons la méthode d'optimisation robuste à 2 niveaux pour le résoudre

Design of VLC and heterogeneous RF/VLC systems for future generation networks: an algorithmic approach

Visible light communication (VLC) has attracted significant research interest within the last decade due in part to the vast amount of unused transmission bandwidth in the visible light spectrum. VLC is expected to be part of future generation networks. The heterogeneous integration of radio frequency (RF) and VLC systems has been envisioned as a promising solution to increase the capacity of wireless networks, especially in indoor environments. However, the promised advantages of VLC and heterogeneous RF/VLC systems cannot be realized without proper resource management algorithms that exploit the distinguishing characteristics between RF and VLC systems. Further, the problem of backhauling for VLC systems has received little attention. This dissertation’s first part focuses on designing and optimizing VLC and heterogeneous RF/VLC systems. Novel resource allocation algorithms that optimize the sum-rate and energy efficiency performances of VLC, hybrid, and aggregated RF/VLC systems while considering practical constraints like illumination requirements, inter-cell interference, quality-of-service requirements, and transmit power budgets are proposed. Moreover, a power line communicationbased backhaul solution for an indoor VLC system is developed, and a backhaul-aware resource allocation algorithm is proposed. These algorithms are developed by leveraging tools from fractional programming (i.e., Dinkelbach’s transform and quadratic transform), the multiplier adjustment method, matching theory, and multi-objective optimization. The latter part of this dissertation examines the adoption of emerging beyond 5G technologies, such as intelligent reflecting surfaces (IRSs) and reconfigurable intelligent surfaces (RISs), to overcome the limitations of VLC systems and boost their performance gains. Novel system models for IRSs-aided and RISs-aided VLC systems are proposed, and metaheuristic-based algorithms are developed to optimize the configurations of the IRSs/RISs and, consequently, the performance of VLC systems. Extensive simulations reveal that the proposed resource allocation schemes outperform the considered benchmarks and provide performance close to the optimal solution. Furthermore, the proposed system models achieve superior performance compared to benchmark system models

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes