Cross-layer Congestion Control, Routing and Scheduling Design in Ad Hoc Wireless Networks

This paper considers jointly optimal design of crosslayer congestion control, routing and scheduling for ad hoc wireless networks. We first formulate the rate constraint and scheduling constraint using multicommodity flow variables, and formulate resource allocation in networks with fixed wireless channels (or single-rate wireless devices that can mask channel variations) as a utility maximization problem with these constraints. By dual decomposition, the resource allocation problem naturally decomposes into three subproblems: congestion control, routing and scheduling that interact through congestion price. The global convergence property of this algorithm is proved. We next extend the dual algorithm to handle networks with timevarying channels and adaptive multi-rate devices. The stability of the resulting system is established, and its performance is characterized with respect to an ideal reference system which has the best feasible rate region at link layer. We then generalize the aforementioned results to a general model of queueing network served by a set of interdependent parallel servers with time-varying service capabilities, which models many design problems in communication networks. We show that for a general convex optimization problem where a subset of variables lie in a polytope and the rest in a convex set, the dual-based algorithm remains stable and optimal when the constraint set is modulated by an irreducible finite-state Markov chain. This paper thus presents a step toward a systematic way to carry out cross-layer design in the framework of “layering as optimization decomposition” for time-varying channel models

On Robust Distributed Control of Transportation Networks

With the ever-growing traffic demands, the transportation networks are getting more and more congested. While expanding these networks with more roads is both costly and in many cities not even feasible, the rapid development of new sensing and communication techniques has made it possible to perform control of transportation networks in real-time. With the right usage of such technologies, existing transportation networks' capacities can be utilized better in order to lower the congestion levels. However, the control has to be done robustly, since real-time control and close to maximal utilization also make the networks more fragile and if not, even a small perturbation can have a tremendous impact on the traffic network. In this thesis, a few solutions that lead to better transportation network utilization are presented, designed with said robustness requirements in mind. In the first part of the thesis, a decentralized control strategy for traffic signals is presented. The proposed policy, which we call Generalized Proportional Allocation (GPA), is inspired by the proportional fairness allocation for communication networks. The original proportional fairness controller does not explicitly take the overhead time needed to shift between different activation phases into account. We, therefore, enhance the proportional fairness so that it adapts its cycle length to the current demand. When the demand is higher, one wants longer signal cycles not to waste too much of the time overhead, while for lower demands, the cycle lengths should be shorter, so that the drivers do not have to wait for a long time. Stability for an averaged version of this control strategy is proved together with throughput-optimality of the controller. This means that no other control strategy can handle larger exogenous inflows to the network than the GPA-controller. Since the traffic signal controllers such as the GPA may allocate service to an empty line, due to the fact that several lanes can receive green light simultaneously, a model that handles this issue is proposed. For this model, the well-posedness of the dynamical system is shown when the traffic signal controller is Lipschitz continuous.The GPA controller's performance is also evaluated in a microscopic traffic simulator. In the microsimulations, it is shown how the proposed feedback controller outperforms the standard fixed-time controller for a scenario based on all traffic over the duration of one full day in Luxembourg. The controller's performance is also compared to another decentralized controller for traffic signals, the MaxPressure controller, for an artificial Manhattan-like network. From these simulations, it can be concluded that the GPA performs better than MaxPressure during low demands, but the MaxPressure performs better when the demand is high. The fact that the GPA does not require any information about the network, apart from the current queue lengths, makes it robust to perturbations. In other words, the control strategy does not have to be updated when the demand or topology of the network changes.The second part of the thesis is devoted to routing problems. First, the problem of routing a fleet of vehicles in an optimal way for the whole fleet is considered. The objective is then to achieve a minimum delay in average for the entire fleet. The routing algorithm takes into account the presence of regular drivers that are trying to optimize their own traveling time in the network. Conditions are posted for when such a routing assignment exists, and two algorithms to compute it are shown.At last, a type of dynamic routing policies for multicommodity flows is studied. The routing policies are designed with the objective to avoid congested routes. It has previously been shown that if only one class of vehicles are present, the network is robust to perturbations with these routing policies. A model for multicommodity flows is proposed, and it is shown that the robustness properties for the single-commodity case do not necessarily hold in the multicommodity case

Random Neural Networks and Optimisation

In this thesis we introduce new models and learning algorithms for the Random Neural Network (RNN), and we develop RNN-based and other approaches for the solution of emergency management optimisation problems. With respect to RNN developments, two novel supervised learning algorithms are proposed. The first, is a gradient descent algorithm for an RNN extension model that we have introduced, the RNN with synchronised interactions (RNNSI), which was inspired from the synchronised firing activity observed in brain neural circuits. The second algorithm is based on modelling the signal-flow equations in RNN as a nonnegative least squares (NNLS) problem. NNLS is solved using a limited-memory quasi-Newton algorithm specifically designed for the RNN case. Regarding the investigation of emergency management optimisation problems, we examine combinatorial assignment problems that require fast, distributed and close to optimal solution, under information uncertainty. We consider three different problems with the above characteristics associated with the assignment of emergency units to incidents with injured civilians (AEUI), the assignment of assets to tasks under execution uncertainty (ATAU), and the deployment of a robotic network to establish communication with trapped civilians (DRNCTC). AEUI is solved by training an RNN tool with instances of the optimisation problem and then using the trained RNN for decision making; training is achieved using the developed learning algorithms. For the solution of ATAU problem, we introduce two different approaches. The first is based on mapping parameters of the optimisation problem to RNN parameters, and the second on solving a sequence of minimum cost flow problems on appropriately constructed networks with estimated arc costs. For the exact solution of DRNCTC problem, we develop a mixed-integer linear programming formulation, which is based on network flows. Finally, we design and implement distributed heuristic algorithms for the deployment of robots when the civilian locations are known or uncertain

Mathematical programming models to design and analyse efficient and robust raiway freight transport networks

(English) Searching to achieve an ambitious reduction in greenhouse gas emissions, the European Union has set as a goal a modal shift in freight transport of 30\% by rail or waterborne for the near future. The increasing efforts of many governments to intensify rail freight transport often must face the difficulties involved in improving both infrastructure and rail operations. Moreover, infrastructure management and business operations usually correspond to different entities with highly contradictory economic interests. Making progress on the reliability of the railway network is one of the main factors to be considered to make the use of the train more attractive as a means of transport for industry. Also, focusing on shippers' response to road and rail competition and the role of different rail undertakings competing with each other may help boost the use of rail for freight transport. Seeking to reinforce these two goals, this thesis introduces two independent mathematical optimisation models, which may also be complementary, and which have been developed under a common conceptual framework of data structures and variables to guarantee their compatibility. The first model is a mathematical programming-based design model for evaluating the impact on a mixed railway network from proposals for infrastructure improvement and capacity expansion that are oriented mainly toward increasing freight transportation. The model has been applied to extend elements of an existing mixed railway network, perform relatively less costly actions on the network, and enhance capacity by adding new blocking/control systems at specific locations. These aspects are usually not considered in models for regional planning. Rather than a model whose sole focus is on railway capacity expansion, this approach combines capacity-expansion with network design. Because the way investments generate returns to the freight transportation system is of utmost relevance for these types of problems, this model is based on the efficient frontier between investment and operating costs. The second model is a combined model for jointly evaluating the modal split road-rail, and the resulting railway freight flows on the railway network. This combined modal split-traffic assignment model is addressed to the case when a modal split based on a random utility model is available, and some of its coefficients may present a non-negligible variability. To this end, after the initial deterministic formulation, a robust counterpart of the model is developed. The model, formulated as a non-linear integer programming problem, is oriented to a multi-carrier environment and includes constraints to consider the interactions between the different types of flows on the railway network, allowing a detailed evaluation of the cost types of the carriers and the network capacity. An algorithmic solution based on the outer approximation method is shown to provide accurate solutions in a reasonable computational time for the robust and non-robust versions of the model. Examples centred on a section of the Trans-European Transport Network, the TEN-T Core network corridors, are reported to test the applicability of the models. Results show the effectiveness of both models. The design model can be a helpful tool for analysing the impact infrastructure investments may have on operating costs, where (implicit) capacity limitations in the scenarios to be evaluated may necessarily be taken into account. At the same time, it can be complemented with the combined modal split-traffic assignment model by assessing the possible shippers' response to the different railway carriers' services competing with each other and the road.(Español) Tratando de lograr una significativa y ambiciosa reducción de las emisiones de gases de efecto invernadero, la Unión Europea se ha marcado como objetivo que los modos de transporte de mercancías alternativos a la carretera, como el ferrocarril o la navegación fluvial, alcancen una cuota del 30% sobre el total de mercancías transportadas por tierra en Europa en los próximos años. Los crecientes esfuerzos que llevan a cabo los diferentes gobiernos se enfrentan con demasiada frecuencia con las dificultades que suponen mejorar de forma simultánea infraestructura y operaciones ferroviarias, habitualmente gestionados por entes diferentes con intereses económicos enfrentados. Mejorar la fiabilidad de la red ferroviaria es uno de los principales factores a tener en cuenta para hacer más atractivo el uso del tren como medio de transporte para la industria. Por otro lado, centrarse en los criterios que pueden llevar a las empresas a elegir entre carretera o tren, y en el papel que juegan las diferentes compañías ferroviarias en esta elección, compitiendo entre sí, puede ayudar a incrementar el uso del tren para el transporte de mercancías. Con la idea de reforzar estos dos objetivos, este trabajo de tesis presenta dos modelos matemáticos de optimización, independientes pero a la vez complementarios, y desarrollados bajo un marco conceptual de estructuras de datos y variables común para garantizar su compatibilidad. El primer modelo es un modelo de diseño basado en programación matemática para evaluar el impacto que pueden tener, sobre una red ferroviaria de uso mixto, propuestas de mejora de la infraestructura y de ampliación de la capacidad dirigidas principalmente a incrementar el uso del tren para el transporte de mercancías. El modelo se ha orientado a la modificación de elementos de una red ferroviaria de uso mixto existente, proponiendo intervenciones en la red relativamente poco costosas, y aumentando la capacidad añadiendo nuevos sistemas de bloqueo y control en ubicaciones específicas. Para este tipo de problemas, es de la máxima relevancia la manera en que las inversiones generan retornos al sistema de transporte ferroviario. Por eso, este modelo está basado en el óptimo equilibrio entre la inversión y los costes de operación. El segundo modelo es un modelo combinado para evaluar de forma conjunta el reparto modal entre carretera y tren, y los flujos de mercancías en la red ferroviaria resultantes. Este modelo está enfocado hacia aquellas situaciones en que hay un modelo de utilidad aleatoria disponible, pero algunos de sus coeficientes pueden presentar una variabilidad que no debe ser ignorada. Con esta finalidad, tras la formulación inicial del modelo determinístico se presenta una versión robusta de la formulación. El modelo, formulado como un problema de programación no lineal entera, está enfocado hacia un entorno en el que conviven (y compiten) diferentes compañías ferroviarias. Se detalla un algoritmo para resolver el modelo, basado en el método de aproximaciones externas, que permite obtener soluciones precisas con un tiempo computacional razonable, tanto para la versión determinística como para la versión robusta. Ejemplos basados en una sección de la Red Trans-Europea de Transporte (TEN-T por sus siglas en inglés) permiten validar la aplicabilidad y eficacia de los modelos. El modelo de diseño puede ser una herramienta útil para analizar el impacto que las inversiones en infraestructura pueden tener en los costes de operación, teniendo en cuenta las limitaciones de capacidad que existen en los escenarios evaluados. De la misma forma, se puede complementar este análisis con el modelo combinado de reparto modal y asignación de flujos, en el que se puede comprobar la posible respuesta de las empresas que requieren transportar sus productos ante los diferentes servicios ofrecidos por las compañías ferroviarias compitiendo entre si, y compitiendo con la carretera.Estadística i investigació operativ

Mathematical programming models to design and analyse efficient and robust raiway freight transport networks

(English) Searching to achieve an ambitious reduction in greenhouse gas emissions, the European Union has set as a goal a modal shift in freight transport of 30\% by rail or waterborne for the near future. The increasing efforts of many governments to intensify rail freight transport often must face the difficulties involved in improving both infrastructure and rail operations. Moreover, infrastructure management and business operations usually correspond to different entities with highly contradictory economic interests. Making progress on the reliability of the railway network is one of the main factors to be considered to make the use of the train more attractive as a means of transport for industry. Also, focusing on shippers' response to road and rail competition and the role of different rail undertakings competing with each other may help boost the use of rail for freight transport. Seeking to reinforce these two goals, this thesis introduces two independent mathematical optimisation models, which may also be complementary, and which have been developed under a common conceptual framework of data structures and variables to guarantee their compatibility. The first model is a mathematical programming-based design model for evaluating the impact on a mixed railway network from proposals for infrastructure improvement and capacity expansion that are oriented mainly toward increasing freight transportation. The model has been applied to extend elements of an existing mixed railway network, perform relatively less costly actions on the network, and enhance capacity by adding new blocking/control systems at specific locations. These aspects are usually not considered in models for regional planning. Rather than a model whose sole focus is on railway capacity expansion, this approach combines capacity-expansion with network design. Because the way investments generate returns to the freight transportation system is of utmost relevance for these types of problems, this model is based on the efficient frontier between investment and operating costs. The second model is a combined model for jointly evaluating the modal split road-rail, and the resulting railway freight flows on the railway network. This combined modal split-traffic assignment model is addressed to the case when a modal split based on a random utility model is available, and some of its coefficients may present a non-negligible variability. To this end, after the initial deterministic formulation, a robust counterpart of the model is developed. The model, formulated as a non-linear integer programming problem, is oriented to a multi-carrier environment and includes constraints to consider the interactions between the different types of flows on the railway network, allowing a detailed evaluation of the cost types of the carriers and the network capacity. An algorithmic solution based on the outer approximation method is shown to provide accurate solutions in a reasonable computational time for the robust and non-robust versions of the model. Examples centred on a section of the Trans-European Transport Network, the TEN-T Core network corridors, are reported to test the applicability of the models. Results show the effectiveness of both models. The design model can be a helpful tool for analysing the impact infrastructure investments may have on operating costs, where (implicit) capacity limitations in the scenarios to be evaluated may necessarily be taken into account. At the same time, it can be complemented with the combined modal split-traffic assignment model by assessing the possible shippers' response to the different railway carriers' services competing with each other and the road.(Español) Tratando de lograr una significativa y ambiciosa reducción de las emisiones de gases de efecto invernadero, la Unión Europea se ha marcado como objetivo que los modos de transporte de mercancías alternativos a la carretera, como el ferrocarril o la navegación fluvial, alcancen una cuota del 30% sobre el total de mercancías transportadas por tierra en Europa en los próximos años. Los crecientes esfuerzos que llevan a cabo los diferentes gobiernos se enfrentan con demasiada frecuencia con las dificultades que suponen mejorar de forma simultánea infraestructura y operaciones ferroviarias, habitualmente gestionados por entes diferentes con intereses económicos enfrentados. Mejorar la fiabilidad de la red ferroviaria es uno de los principales factores a tener en cuenta para hacer más atractivo el uso del tren como medio de transporte para la industria. Por otro lado, centrarse en los criterios que pueden llevar a las empresas a elegir entre carretera o tren, y en el papel que juegan las diferentes compañías ferroviarias en esta elección, compitiendo entre sí, puede ayudar a incrementar el uso del tren para el transporte de mercancías. Con la idea de reforzar estos dos objetivos, este trabajo de tesis presenta dos modelos matemáticos de optimización, independientes pero a la vez complementarios, y desarrollados bajo un marco conceptual de estructuras de datos y variables común para garantizar su compatibilidad. El primer modelo es un modelo de diseño basado en programación matemática para evaluar el impacto que pueden tener, sobre una red ferroviaria de uso mixto, propuestas de mejora de la infraestructura y de ampliación de la capacidad dirigidas principalmente a incrementar el uso del tren para el transporte de mercancías. El modelo se ha orientado a la modificación de elementos de una red ferroviaria de uso mixto existente, proponiendo intervenciones en la red relativamente poco costosas, y aumentando la capacidad añadiendo nuevos sistemas de bloqueo y control en ubicaciones específicas. Para este tipo de problemas, es de la máxima relevancia la manera en que las inversiones generan retornos al sistema de transporte ferroviario. Por eso, este modelo está basado en el óptimo equilibrio entre la inversión y los costes de operación. El segundo modelo es un modelo combinado para evaluar de forma conjunta el reparto modal entre carretera y tren, y los flujos de mercancías en la red ferroviaria resultantes. Este modelo está enfocado hacia aquellas situaciones en que hay un modelo de utilidad aleatoria disponible, pero algunos de sus coeficientes pueden presentar una variabilidad que no debe ser ignorada. Con esta finalidad, tras la formulación inicial del modelo determinístico se presenta una versión robusta de la formulación. El modelo, formulado como un problema de programación no lineal entera, está enfocado hacia un entorno en el que conviven (y compiten) diferentes compañías ferroviarias. Se detalla un algoritmo para resolver el modelo, basado en el método de aproximaciones externas, que permite obtener soluciones precisas con un tiempo computacional razonable, tanto para la versión determinística como para la versión robusta. Ejemplos basados en una sección de la Red Trans-Europea de Transporte (TEN-T por sus siglas en inglés) permiten validar la aplicabilidad y eficacia de los modelos. El modelo de diseño puede ser una herramienta útil para analizar el impacto que las inversiones en infraestructura pueden tener en los costes de operación, teniendo en cuenta las limitaciones de capacidad que existen en los escenarios evaluados. De la misma forma, se puede complementar este análisis con el modelo combinado de reparto modal y asignación de flujos, en el que se puede comprobar la posible respuesta de las empresas que requieren transportar sus productos ante los diferentes servicios ofrecidos por las compañías ferroviarias compitiendo entre si, y compitiendo con la carretera.Postprint (published version

Networks, Communication, and Computing Vol. 2

Networks, communications, and computing have become ubiquitous and inseparable parts of everyday life. This book is based on a Special Issue of the Algorithms journal, and it is devoted to the exploration of the many-faceted relationship of networks, communications, and computing. The included papers explore the current state-of-the-art research in these areas, with a particular interest in the interactions among the fields

High-Performance Broadcast and Multicast Protocols for Multi-Radio Multi-Channel Wireless Mesh Networks

Recently, wireless mesh networks (WMNs) have attracted much attention. A vast amount of unicast, multicast and broadcast protocols has been developed for WMNs or mobile ad hoc networks (MANETs). First of all, broadcast and multicast in wireless networks are fundamentally different from the way in which wired networks function due to the well-known wireless broadcast/multicast advantage. Moreover, most broadcast and multicast protocols in wireless networks assume a single-radio single-channel and single-rate network model, or a generalized physical model, which does not take into account the impact of interference. This dissertation focuses on high-performance broadcast and multicast protocols designed for multi-radio multi-channel (MRMC) WMNs. MRMC increases the capacity of the network from different aspects. Multi-radio allows mesh nodes to simultaneously send and receive through different radios to its neighbors. Multi-channel allows channels to be reused across the network, which expands the available spectrum and reduces the interference. Unlike MANETs, WMNs are assumed to be static or with minimal mobility. Therefore, the main design goal in WMNs is to achieve high throughput rather than to maintain connectivity. The capacity of WMNs is constrained by the interference caused by the neighbor nodes. One direct design objective is to minimize or reduce the interference in broadcast and multicast. This dissertation presents a set of broadcast and multicast protocols and mathematical formulations to achieve the design goal in MRMC WMNs. First, the broadcast problem is addressed with full consideration of both inter-node and intra-node interference to achieve efficient broadcast. The interference-aware broadcast protocol simultaneously achieves full reliability, minimum broadcast or multicast latency, minimum redundant transmissions, and high throughput. With an MRMC WMN model, new link and channel quality metrics are defined and are suitable for the design of broadcast and multicast protocols. Second, the minimum cost broadcast problem (MCBP), or minimum number of transmissions problem, is studied for MRMC WMNs. Minimum cost broadcast potentially allows more effective and efficient schedule algorithms to be designed. The proposed protocol with joint consideration of channel assignment reduces the interference to improve the throughput in the MCBP. Minimum cost broadcast in MRMC WMNs is very different from that in the single radio single channel scenario. The channel assignment in MRMC WMNs is used to assign multiple radios of every node to different channels. It determines the actual network connectivity since adjacent nodes have to be assigned to a common channel. Transmission on different channels makes different groups of neighboring nodes, and leads to different interference. Moreover, the selection of channels by the forward nodes impacts on the number of radios needed for broadcasting. Finally, the interference optimization multicast problem in WMNs with directional antennas is discussed. Directional transmissions can greatly reduce radio interference and increase spatial reuse. The interference with directional transmissions is defined for multicast algorithm design. Multicast routing found by the interference-aware algorithm tends to have fewer channel collisions. The research work presented in this dissertation concludes that (1) new and practical link and channel metrics are required for designing broadcast and multicast in MRMC WMNs; (2) a small number of radios is sufficient to significantly improve throughput of broadcast and multicast in WMNs; (3) the number of channels has more impact on almost all performance metrics, such as the throughput, the number of transmission, and interference, in WMNs

Conjoint Routing and Resource Allocation in OFDMA-based D2D Wireless Networks

In this paper, we develop a highly efficient twotier technique for jointly optimizing the routes, the subcarrier schedules, th

Optimization for Decision Making II

In the current context of the electronic governance of society, both administrations and citizens are demanding the greater participation of all the actors involved in the decision-making process relative to the governance of society. This book presents collective works published in the recent Special Issue (SI) entitled “Optimization for Decision Making II”. These works give an appropriate response to the new challenges raised, the decision-making process can be done by applying different methods and tools, as well as using different objectives. In real-life problems, the formulation of decision-making problems and the application of optimization techniques to support decisions are particularly complex and a wide range of optimization techniques and methodologies are used to minimize risks, improve quality in making decisions or, in general, to solve problems. In addition, a sensitivity or robustness analysis should be done to validate/analyze the influence of uncertainty regarding decision-making. This book brings together a collection of inter-/multi-disciplinary works applied to the optimization of decision making in a coherent manner

Métaheuristiques de recherche avec tabous pour le problème de synthèse de réseau multiproduits avec capacités

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal