Randomized rounding algorithms for large scale unsplittable flow problems

Unsplittable flow problems cover a wide range of telecommunication and transportation problems and their efficient resolution is key to a number of applications. In this work, we study algorithms that can scale up to large graphs and important numbers of commodities. We present and analyze in detail a heuristic based on the linear relaxation of the problem and randomized rounding. We provide empirical evidence that this approach is competitive with state-of-the-art resolution methods either by its scaling performance or by the quality of its solutions. We provide a variation of the heuristic which has the same approximation factor as the state-of-the-art approximation algorithm. We also derive a tighter analysis for the approximation factor of both the variation and the state-of-the-art algorithm. We introduce a new objective function for the unsplittable flow problem and discuss its differences with the classical congestion objective function. Finally, we discuss the gap in practical performance and theoretical guarantees between all the aforementioned algorithms

Resource management and scheduling for a broadband telecommunications system : Optimization of satellite bandwidth

Les télécommunications par satellite ont connu ces dernières années un regain d'intérêt important, du fait de leur capacité à permettre la réduction de la fracture numérique. En effet, un satellite en orbite géostationnaire peut s'appuyer sur une très grande couverture et une capacité importante pour atteindre des zones où le déploiement des réseaux terrestres n'est pas envisageable, comme les transports (bateau, avion), ou bien les zones blanches, où il serait difficilement rentable. Traditionnellement concentrés sur la diffusion de télévision numérique, les dernières générations de standards reflètent cet engouement en faisant une place de choix à la transmission de données bidirectionnelle, notamment en permettant une prise en charge simple des protocoles de l'Internet. Le problème de l'ordonnancement dans ces systèmes devient alors particulièrement important, puisqu'il doit prendre en compte deux processus évoluant de manière totalement décorrélée. D'un côté, l'évolution de la demande des utilisateurs, dépendante des applications (vidéo, voix, données). De l'autre, l'évolution de la capacité du système, celle-ci étant tributaire des conditions de transmission : les fréquences utilisées dans ces systèmes sont particulièrement sensibles à l'atténuation due à l'eau dans l'atmosphère. Cette thèse s'intéresse au problème de l'ordonnancement et de l'allocation de ressources, dans le but de fournir un service comparable aux réseaux terrestres en termes de services, en présentant les meilleures performances possibles. Si un certain nombre de propositions ont été faites sur le sujet, aucune ne prend en compte l'ensemble des contraintes d'un tel système. Outre le caractère variable de la capacité, la variabilité de la demande, conjuguée avec les contraintes de qualité de service constitue une difficulté supplémentaire. Enfin, il nous faut considérer la faisabilité de notre solution dans un contexte temps réel, nécessaire dans l'optique d'une implantation dans un système réel. Nous avons ainsi développé une architecture d'ordonnanceur pour la voie Aller, reposant sur des fonctions d'utilité, permettant ainsi une formulation simple du compromis entre demande et capacité. Nous montrons comment cet algorithme pourrait être utilisable dans un système complet, à travers une implantation détaillée, de faible complexité, ainsi que des simulations de cas réels. Nous portons ensuite notre attention sur la voie Retour, où nous proposons une méthode d'allocation de ressources prenant en compte de manière conjointe la qualité de service et la qualité du support pour délivrer une allocation à la fois conforme et performante. Les simulations montrent que notre algorithme obtient une efficacité et une meilleure gestion du trafic que des solutions de référence présentées dans la littérature.Satellite telecommunications have seen a tremendous increase in interest, due to its ability to reduce the digital divide. In fact, a geostationary satellite can take advantage of its very wide coverage and high capacity to reach areas where deployment of a terrestrial network would not be possible, such as transports, or too expensive to be profitable, as in remote areas. Traditionally focused on digital television broadcasting, the latest generation of standards have evolved to reflect those new needs, dealing extensively with the transmission of interactive data, particularly by natively supporting Internet protocols. Scheduling has arisen as a major issue of those modern systems, since it has to deal with to highly uncorrelated processes: demand and capacity. Demand, on one side, evolves with user's needs, and therefore with the applications they are using: video, voice or data. Capacity, on the other side, depends on meteorological conditions over the satellite's cover, as the frequencies used in such systems are very sensitive to wet atmosphere attenuation. This thesis aims to study the problem of scheduling and resource allocation, hoping to achieve a service that can match with terrestrial networks in terms of services, while showing the best possible performances. If numerous solutions were proposed on this topic, none is taking into account all of the current system's constraints. In addition to the variable nature of system's capacity, the conjunction of variable demand and quality of service constraints constitutes an additional issue. Furthermore, we have to consider the practicability of our solution in a real-time context, necessary if we aim for industrial use. We have first developed a scheduler architecture for the Forward link, based on utility functions, thus allowing a simple formulation of the capacity versus demand compromise. We show, through a detailed low-complexity implementation and accurate simulations, how our algorithm could be used efficiently in an industrial context. We then focus on the Return link, where we propose a resource allocation method, taking into account quality of service and quality of transmission jointly to deliver an efficient yet consistent resource allocation. Simulations show that our algorithm achieves a better efficiency and traffic handling than reference solutions presented in the literature

Complexity analysis for recent ALOHA random access techniques in satellite communications

International audienceIn this paper we study the the complexity of packet localization at reception, for recent synchronous Random Access (RA) techniques based on the protocol ALOHA for satellite communications. The promising CRDSA (Contention Resolution Diversity Slotted ALOHA) offers better throughput, in comparison to the traditional slotted ALOHA protocols, thanks to the use of Successive Interference Cancellation (SIC) along with multireplica transmission. MARSALA (Multi-replicA decoding using corRelation baSed locALizAtion) is one of the many variants and enhancement schemes of CRDSA that have been proposed in the literature. It is applied to CRDSA each time a decoding deadlock situation is reached (when no packets can be retrieved by CRDSA). MARSALA first localizes the replicas of collided packets on a chosen reference time slot using correlations. Then it performs coherent signal combination of packet replicas prior to decoding. However, despite the good performance offered by MARSALA, its localization process adds a significant complexity to the receiver in terms of correlation operations. R-SPOTiT (Random Shared POsition Technique for Interfered random Transmissions) mitigates this complexity by introducing a shared information between the receiver and each of the transmitters, about all potential packets' locations on the frame, without any additional signaling overhead. We focus in this paper on the analysis of the total number of correlations which are needed to localize packets' replicas for both MARSALA and R-SPOTiT, with a single or with multiple Gold preambles. This should include preamble detection operations that are performed at CRDSA with a coarse and fine tracking. The results show that the most suitable system to use is the multi-preamble R-SPOTiT with two preambles