Dissertations / Theses on the topic 'Dynamic allocation of ressources'
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Lyazidi, Mohammed Yazid. "Dynamic resource allocation and network optimization in the Cloud Radio Access Network." Electronic Thesis or Diss., Paris 6, 2017. http://www.theses.fr/2017PA066549.
Cloud Radio Access Network (C-RAN) is a future direction in wireless communications for deploying cellular radio access subsystems in current 4G and next-generation 5G networks. In the C-RAN architecture, BaseBand Units (BBUs) are located in a pool of virtual base stations, which are connected via a high-bandwidth low latency fronthaul network to Radio Remote Heads (RRHs). In comparison to standalone clusters of distributed radio base stations, C-RAN architecture provides significant benefits in terms of centralized resource pooling, network flexibility and cost savings. In this thesis, we address the problem of dynamic resource allocation and power minimization in downlink communications for C-RAN. Our research aims to allocate baseband resources to dynamic flows of mobile users, while properly assigning RRHs to BBUs to accommodate the traffic and network demands. This is a non-linear NP-hard optimization problem, which encompasses many constraints such as mobile users' resources demands, interference management, BBU pool and fronthaul links capacities, as well as maximum transmission power limitation. To overcome the high complexity involved in this problem, we present several approaches for resource allocation strategies and tackle this issue in three stages. Obtained results prove the efficiency of our proposed strategies in terms of throughput satisfaction rate, number of active RRHs, BBU pool processing power, resiliency, and operational budget cost
Lyazidi, Mohammed Yazid. "Dynamic resource allocation and network optimization in the Cloud Radio Access Network." Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066549/document.
Cloud Radio Access Network (C-RAN) is a future direction in wireless communications for deploying cellular radio access subsystems in current 4G and next-generation 5G networks. In the C-RAN architecture, BaseBand Units (BBUs) are located in a pool of virtual base stations, which are connected via a high-bandwidth low latency fronthaul network to Radio Remote Heads (RRHs). In comparison to standalone clusters of distributed radio base stations, C-RAN architecture provides significant benefits in terms of centralized resource pooling, network flexibility and cost savings. In this thesis, we address the problem of dynamic resource allocation and power minimization in downlink communications for C-RAN. Our research aims to allocate baseband resources to dynamic flows of mobile users, while properly assigning RRHs to BBUs to accommodate the traffic and network demands. This is a non-linear NP-hard optimization problem, which encompasses many constraints such as mobile users' resources demands, interference management, BBU pool and fronthaul links capacities, as well as maximum transmission power limitation. To overcome the high complexity involved in this problem, we present several approaches for resource allocation strategies and tackle this issue in three stages. Obtained results prove the efficiency of our proposed strategies in terms of throughput satisfaction rate, number of active RRHs, BBU pool processing power, resiliency, and operational budget cost
Jmila, Houda. "Dynamic resource allocation and management in virtual networks and Clouds." Electronic Thesis or Diss., Evry, Institut national des télécommunications, 2015. http://www.theses.fr/2015TELE0023.
Cloud computing is a promising technology enabling IT resources reservation and utilization on a pay-as-you-go manner. In addition to the traditional computing resources, cloud tenants expect compete networking of their dedicated resources to easily deploy network functions and services. They need to manage an entire Virtual Network (VN) or infrastructure. Thus, Cloud providers should deploy dynamic and adaptive resource provisioning solutions to allocate virtual networks that reflect the time-varying needs of Cloud-hosted applications. Prior work on virtual network resource provisioning only focused on the problem of mapping the virtual nodes and links composing a virtual network request to the substrate network nodes and paths, known as the Virtual network embedding (VNE) problem. Little attention was paid to the resource management of the allocated resources to continuously meet the varying demands of embedded virtual networks and to ensure efficient substrate resource utilization. The aim of this thesis is to enable dynamic and preventive virtual network resources provisioning to deal with demand fluctuation during the virtual network lifetime, and to enhance the substrate resources usage. To reach these goals, the thesis proposes adaptive resource allocation algorithms for evolving virtual network requests. We adress the extension of an embedded virtual node requiring more resources and consider the substrate network profitability. We also deal with the bandwidth demand variation in embedded virtual links. We first provide a heuristic algorithm to deal with virtual nodes demand fluctuation. The work is extended by designing a preventive re-configuration scheme to enhance substrate network profitability. Finally, a distributed, local-view and parallel framework was devised to handle embedded virtual links bandwidth fluctuations. The approach is composed of a controller and three algorithms running in each substrate node in a distributed and parallel manner. The framework is based on the self-stabilization approach, and can manage various forms of bandwidth demand variations simultaneously
Jmila, Houda. "Dynamic resource allocation and management in virtual networks and Clouds." Thesis, Evry, Institut national des télécommunications, 2015. http://www.theses.fr/2015TELE0023/document.
Cloud computing is a promising technology enabling IT resources reservation and utilization on a pay-as-you-go manner. In addition to the traditional computing resources, cloud tenants expect compete networking of their dedicated resources to easily deploy network functions and services. They need to manage an entire Virtual Network (VN) or infrastructure. Thus, Cloud providers should deploy dynamic and adaptive resource provisioning solutions to allocate virtual networks that reflect the time-varying needs of Cloud-hosted applications. Prior work on virtual network resource provisioning only focused on the problem of mapping the virtual nodes and links composing a virtual network request to the substrate network nodes and paths, known as the Virtual network embedding (VNE) problem. Little attention was paid to the resource management of the allocated resources to continuously meet the varying demands of embedded virtual networks and to ensure efficient substrate resource utilization. The aim of this thesis is to enable dynamic and preventive virtual network resources provisioning to deal with demand fluctuation during the virtual network lifetime, and to enhance the substrate resources usage. To reach these goals, the thesis proposes adaptive resource allocation algorithms for evolving virtual network requests. We adress the extension of an embedded virtual node requiring more resources and consider the substrate network profitability. We also deal with the bandwidth demand variation in embedded virtual links. We first provide a heuristic algorithm to deal with virtual nodes demand fluctuation. The work is extended by designing a preventive re-configuration scheme to enhance substrate network profitability. Finally, a distributed, local-view and parallel framework was devised to handle embedded virtual links bandwidth fluctuations. The approach is composed of a controller and three algorithms running in each substrate node in a distributed and parallel manner. The framework is based on the self-stabilization approach, and can manage various forms of bandwidth demand variations simultaneously
Morcos, Mira. "Auction-based dynamic resource orchestration in cloud-based radio access networks." Electronic Thesis or Diss., Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLL003.
Network densification using small cells massively deployed over the macro-cell areas, represents a promising solution for future 5G mobile networks to cope with mobile traffic increase. In order to simplify the management of the heterogeneous Radio Access Network (RAN) that results from the massive deployment of small cells, recent research and industrial studies have promoted the design of novel centralized RAN architectures termed as Cloud-RAN (C-RAN), or Virtual RAN (V-RAN), by incorporating the benefits of cloud computing and Network Functions Virtualization (NFV). The DynaRoC project aims at (1) developing a theoretical framework of resource orchestration for C-RAN and deriving the fundamental performance limits as well as the tradeoffs among various system parameters, and (2) designing dynamic resource orchestration mechanisms based on the theoretical findings to achieve a desired performance balance, by taking into account various design challenges. The PhD student will investigate innovative resource optimization mechanisms to foster the deployment of C-RANs, improving their performance exploiting the enabling Network Functions Virtualization technology
Morcos, Mira. "Auction-based dynamic resource orchestration in cloud-based radio access networks." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLL003.
Network densification using small cells massively deployed over the macro-cell areas, represents a promising solution for future 5G mobile networks to cope with mobile traffic increase. In order to simplify the management of the heterogeneous Radio Access Network (RAN) that results from the massive deployment of small cells, recent research and industrial studies have promoted the design of novel centralized RAN architectures termed as Cloud-RAN (C-RAN), or Virtual RAN (V-RAN), by incorporating the benefits of cloud computing and Network Functions Virtualization (NFV). The DynaRoC project aims at (1) developing a theoretical framework of resource orchestration for C-RAN and deriving the fundamental performance limits as well as the tradeoffs among various system parameters, and (2) designing dynamic resource orchestration mechanisms based on the theoretical findings to achieve a desired performance balance, by taking into account various design challenges. The PhD student will investigate innovative resource optimization mechanisms to foster the deployment of C-RANs, improving their performance exploiting the enabling Network Functions Virtualization technology
Luu, Quang Trung. "Dynamic Control and Optimization of Wireless Virtual Networks." Electronic Thesis or Diss., université Paris-Saclay, 2021. http://www.theses.fr/2021UPASG039.
Network slicing is a key enabler for 5G networks. With network slicing, Mobile Network Operators (MNO) create various slices for Service Providers (SP) to accommodate customized services. As network slices are operated on a common network infrastructure owned by some Infrastructure Provider (InP), efficiently sharing the resources across various slices is very important. In this thesis, taking the InP perspective, we propose several methods for provisioning resources for network slices. Previous best-effort approaches deploy the various Service Function Chains (SFCs) of a given slice sequentially in the infrastructure network. In this thesis, we provision aggregate resources to accommodate slice demands. Once provisioning is successful, the SFCs of the slice are ensured to get enough resources to be properly operated. This facilitates the satisfaction of the slice quality of service requirements. The proposed provisioning solutions also yield a reduction of the computational resources needed to deploy the SFCs
Unlu, Eren. "Dynamic Bandwidth allocation algorithms for an RF on-chip interconnect." Thesis, CentraleSupélec, 2016. http://www.theses.fr/2016SUPL0006/document.
With rapidly increasing number of cores on a single chip, scalability problems have arised due to congestion and latency with conventional interconnects. In order to address these issues, WiNoCoD project (Wired RF Network-on-Chip Reconfigurable-on-Demand) has been initiated by the support of French National Research Agency (ANR). This thesis work contributes to WiNoCoD project. A special RF controller structure has been proposed for the OFDMA based wired RF interconnect of WiNoCoD. Based on this architecture, effective bandwidth allocation algorithms have been presented, concerning very specific requirements and constraints of on-chip environment. An innovative subcarrier allocation protocol for bimodal packet lengths of cache coherency traffic has been presented, which is proven to decrease average latency significantly. In addition to these, effective modulation order selection policies for this interconnect have been introduced, which seeks the optimal delay-power trade-off
Avranas, Apostolos. "Resource allocation for latency sensitive wireless systems." Electronic Thesis or Diss., Institut polytechnique de Paris, 2020. http://www.theses.fr/2020IPPAT021.
The new generation of wireless systems 5G aims not only to convincingly exceed its predecessor (LTE) data rate but to work with more dimensions. For instance, more user classes were introduced associated with different available operating points on the trade-off of data rate, latency, reliability. New applications, including augmented reality, autonomous driving, industry automation and tele-surgery, push the need for reliable communications to be carried out under extremely stringent latency constraints. How to manage the physical level in order to successfully meet those service guarantees without wasting valuable and expensive resources is a hard question. Moreover, as the permissible communication latencies shrink, allowing retransmission protocol within this limited time interval is questionable. In this thesis, we first pursue to answer those two questions. Concentrating on the physical layer and specifically on a point to point communication system, we aim to answer if there is any resource allocation of power and blocklength that will render an Hybrid Automatic ReQuest (HARQ) protocol with any number of retransmissions beneficial. Unfortunately, the short latency requirements force only a limited number of symbols to possibly be transmitted which in its turn yields the use of the traditional Shannon theory inaccurate. Hence, the more involved expression using finite blocklength theory must be employed rendering the problem substantially more complicate. We manage to solve the problem firstly for the additive white gaussian noise (AWGN) case after appropriate mathematical manipulations and the introduction of an algorithm based on dynamic programming. Later we move on the more general case where the signal is distorted by a Ricean channel fading. We investigate how the scheduling decisions are affected given the two opposite cases of Channel State Information (CSI), one where only the statistical properties of the channel is known, i.e. statistical CSI, and one where the exact value of the channel is provided to the transmitter, i.e., full CSI.Finally we ask the same question one layer above, i.e. the Medium Access Contron (MAC). The resource allocation must be performed now accross multiple users. The setup for each user remains the same, meaning that a specific amount of information must be delivered successfully under strict latency constraints within which retransmissions are allowed. As 5G categorize users to different classes users according to their needs, we model the traffic under the same concept so each user belongs to a different class defining its latency and data needs. We develop a deep reinforcement learning algorithm that manages to train a neural network model that competes conventional approaches using optimization or combinatorial algorithms. In our simulations, the neural network model actually manages to outperform them in both statistical and full CSI case
Zehendner, Elisabeth. "Operations management at container terminals using advanced information technologies." Phd thesis, Ecole Nationale Supérieure des Mines de Saint-Etienne, 2013. http://tel.archives-ouvertes.fr/tel-00972071.
Baccouche, Leila. "Un mécanisme d'ordonnancement distribue de taches temps réel." Grenoble INPG, 1995. http://tel.archives-ouvertes.fr/tel-00004976.
Dawaliby, Samir. "Machine-to-Machine (M2M) Communications in Next Generation Networks : Spectrum management and energy efficiency." Thesis, Poitiers, 2019. http://www.theses.fr/2019POIT2280.
This thesis deals with the problem of guaranteeing heterogeneous quality of service (QoS) requirements for Internet of Things (IoT) communications in terms of urgency and reliability. Various solutions are proposed towards achieving this goal in LoRa Wide Area Networks (LoRaWAN). First, we implement network slicing over LoRa standard architecture and evaluate its impact using various static and dynamic strategies. Simulation Results performed over NS3 proved the efficiency of network slicing in isolating physical resources for each slice and serving delay critical communications. Motivated by these results, a slice-based optimization is proposed next to improve the dynamic slicing strategy by investigating more LoRa parameters at the physical layer. The proposed method finds for each device the best parameters configuration that potentially improves the performance of its slice in terms of QoS, reliability and energy efficiency. Moreover, we also looked towards meeting upcoming challenges in future IoT networks that comes from the increasing number of IoT devices. Even with network slicing, LoRa scalability remained as a big challenge that should be carefully considered especially due to the lack of flexibility in managing current wireless networks. Therefore, to meet the global objective in guaranteeing QoS in large scale IoT deployments, software defined networking (SDN) and network slicing are adopted as backbone technologies for a distributed virtualized architecture and slicing strategy. The latter proposition is based on game theory and adapts faster to the changes in a congested IoT environment by leveraging slicing decision making closer to the edge
Obando, Bravo German Dario. "Distributed methods for resource allocation : a passivity based approach." Thesis, Nantes, Ecole des Mines, 2015. http://www.theses.fr/2015EMNA0174/document.
Since the complexity and scale of systems have been growing in the last years, distributed approaches for control and decision making are becoming more prevalent. This dissertation focuses on an important problem involving distributed control and decision making, the dynamic resource allocation in a network. To address this problem, we explore a consensus--based algorithm that does not require any centralized computation, and that is capable to deal with applications modeled either by dynamical systems or by memoryless functions. The main contribution of our research is to prove, by means of graph theoretical tools and passivity analysis, that the proposed controller asymptotically reaches an optimal solution without the need of full information. In order to illustrate the relevance of our main result, we address several engineering applications including: distributed control for energy saving in smart buildings, management of the customers of an aggregating entity in a smart grid environment, and development of an exact distributed optimization method that deals with resource allocation problems subject to lower--bound constraints. Finally, we explore resource allocation techniques based on classic population dynamics models. In order to make them distributed, we introduce the concept of non--well--mixed population dynamics. We show that these dynamics are capable to deal with constrained information structures that are characterized by non--complete graphs. Although the proposed non--well--mixed population dynamics use partial information, they preserve similar properties of their classic counterpart, which uses full information. Specifically, we prove mass conservation and convergence to Nash equilibrium
Dado que la complejidad y la escala de los sistemas sehan ido incrementando en los últimos años, las técnicas centralizadas de control y toma de decisiones están siendo reemplazadas por métodos distribuidos. Esta tesis se centra en un importante problema que involucra control y toma de decisiones distribuidas: la asignación dinámica de recursos en redes. Para abordar este problema, exploramos un algoritmo basado en consenso que no requiere computación centralizada, y que puede ser usado en aplicaciones modeladas ya sea por sistemas dinámicos o funciones sin memoria. La principal contribución de esta tesis es probar, por medio de teoría de grafos y pasividad, que el algoritmo propuesto alcanza asintóticamente una solución óptima sin la necesidad de usar información completa. Para ilustrar la relevancia del resultado principal de esta disertación, abordamos varias aplicaciones en ingeniería,incluyendo: el control distribuido en edificios inteligentes orientado a la eficiencia energética, la gestión de los clientes de un agregador en una red inteligente en la que se aplican estrategias de respuesta de la demanda, y el desarrollo de un método de optimización exacto que permite incluir restricciones de límite inferior. Finalmente, se exploran otras técnicas de asignación derecursos inspiradas en modelos de dinámicas poblacionales. Se introduce el concepto de poblaciones no—bien—mezcladas, y se muestra que las dinámicas asociadas a este tipo de poblaciones cuentan con una estructura de información local, caracterizada por grafos que no son completos. A pesar de que las dinámicas propuestas usan información parcial, ellas preservan características similares a las dinámicas poblacionales clásicas que usan información completa
Malik, Shahzad Ali. "Allocation de ressource radio et analyse de performance pour l'offre de services multimédia dans les réseaux cellulaires UMTS WCDMA." Paris, ENST, 2002. http://www.theses.fr/2002ENSTA004.
Hammami, Seif Eddine. "Dynamic network resources optimization based on machine learning and cellular data mining." Electronic Thesis or Diss., Evry, Institut national des télécommunications, 2018. http://www.theses.fr/2018TELE0015.
Real datasets of mobile network traces contain valuable information about the network resources usage. These traces may be used to enhance and optimize the network performances. A real dataset of CDR (Call Detail Records) traces, that include spatio-temporal information about mobile users’ activities, are analyzed and exploited in this thesis. Given their large size and the fact that these are real-world datasets, information extracted from these datasets have intensively been used in our work to develop new algorithms that aim to revolutionize the infrastructure management mechanisms and optimize the usage of resource. We propose, in this thesis, a framework for network profiles classification, load prediction and dynamic network planning based on machine learning tools. We also propose a framework for network anomaly detection. These frameworks are validated using different network topologies such as wireless mesh networks (WMN) and drone-cell based networks. We show that using advanced data mining techniques, our frameworks are able to help network operators to manage and optimize dynamically their networks
Elkael, Maxime. "Reinforcement learning and optimization for energy efficient 5G slicing with Quality of Service guarantees." Electronic Thesis or Diss., Institut polytechnique de Paris, 2023. http://www.theses.fr/2023IPPAS015.
This thesis addresses resource allocation problems in 5G networks. Our objective is to leverage network slicing (e.g. the set of techniques based on virtualization and network softwarization which allows the network operator to provide different amounts of resources to different tenants) in order to to improve the energy-efficiency and resource consumption of 5G networks, while guaranteeing Quality of Service constraints. To do so, we formulate and solve optimization problems at the different domains of the network: We are first concerned with the placement of slices in the core network. To solve the problem, a new approach combining Monte Carlo Search and Neighborhood Search is formulated. We show it accepts more core slices than state-of-the-art approaches for the core network placement problem. Then we shift the focus to energy efficiency in resource allocation in 5G networks shared between Physical Network Operators (PNOs) and Mobile Virtual Network Operators (MVNOs). This framework jointly considers software component placement, user request routing, and resource dimensioning while meeting Service Level Agreements (SLAs) based on latency and reliability constraints. Through Column Generation, we obtain exact solutions, demonstrating energy savings of up to 50% in real networks compared to existing placement or resource minimization algorithms. Finally, we delve into the realm of energy optimization in Integrated Access and Backhaul (IAB) networks, a key component of dense 5G deployments. Leveraging the Open Radio Access Network (O-RAN) framework, our model minimizes active IAB nodes while ensuring a minimum capacity for User Equipment (UE). Formulated as a binary nonlinear program, this approach reduces RAN energy consumption by 47%, while maintaining Quality-Of-Service for UEs. Overall, this thesis provides novel algorithms for improving resource and energy efficiency of 5G network slicing. Such improvement is studied in different parts of the network, from the core up to the access network
Hammami, Seif Eddine. "Dynamic network resources optimization based on machine learning and cellular data mining." Thesis, Evry, Institut national des télécommunications, 2018. http://www.theses.fr/2018TELE0015/document.
Real datasets of mobile network traces contain valuable information about the network resources usage. These traces may be used to enhance and optimize the network performances. A real dataset of CDR (Call Detail Records) traces, that include spatio-temporal information about mobile users’ activities, are analyzed and exploited in this thesis. Given their large size and the fact that these are real-world datasets, information extracted from these datasets have intensively been used in our work to develop new algorithms that aim to revolutionize the infrastructure management mechanisms and optimize the usage of resource. We propose, in this thesis, a framework for network profiles classification, load prediction and dynamic network planning based on machine learning tools. We also propose a framework for network anomaly detection. These frameworks are validated using different network topologies such as wireless mesh networks (WMN) and drone-cell based networks. We show that using advanced data mining techniques, our frameworks are able to help network operators to manage and optimize dynamically their networks
Mallen-Pisano, Jérémy. "Dynamique de la productivité et efficience allocative des marchés : Une analyse appliquée à l'industrie française." Thesis, Nice, 2013. http://www.theses.fr/2013NICE0055/document.
We research a link between the market selection effects and the productivity growth in the French manufacturing industry. Generally, we suppose that the French market has an allocative inefficiency, especially when comparing it with the American market. To appreciate this hypothesis, we suggest an empirical approach based on recent theoretical contributions in the fields of industrial dynamics, in particular when looking at market distortions and heterogeneous firms within the monopolistic competition models. All work proposals are based on Firm Annual Survey (EAE) data. This Database covers all French manufacturing firms which have more than 20 employees from 1990 to 2006. Overall, our results do not sustain our research hypothesis. Indeed, we find that the market selection effects have strongly contributed to the productivity growth of the French manufacturing industries, in particular in the recent period. On another side, we show that the most recent methods do not allow discriminating between the French manufacturing industries and the American manufacturing industries according to the efficiency criteria of the intrasectoriel resources reallocation process. Finally, we suggest different ways to go further, such as using theoretical dynamic tools including inefficiency allocative measures
Granger, Thierry. "Allocation des ressources avec communication limitée." Paris 9, 1992. https://portail.bu.dauphine.fr/fileviewer/index.php?doc=1992PA090008.
The object of this thesis is the endogeneisation of communication systems in the economy. The first part is devoted to the measures and costs of communication. The "revelation principle" of games with complete or incomplete informations is developed critically in the second part where different classical organizations are examined communication-wise
Wilczynski, Anaëlle. "Interaction entre agents modélisée par un réseau social dans des problématiques de choix social computationnel Strategic Voting in a Social Context: Considerate Equilibria Object Allocation via Swaps along a Social Network Local Envy-Freeness in House Allocation Problems Constrained Swap Dynamics over a Social Network in Distributed Resource Reallocation Poll-Confident Voters in Iterative Voting." Thesis, Paris Sciences et Lettres (ComUE), 2018. http://www.theses.fr/2018PSLED073.
Social choice is the study of collective decision making, where a set of agents must make a decision over a set of alternatives, according to their preferences. The question relies on how aggregating the preferences of the agents in order to end up with a decision that is commonly acceptable for the group. Typically, agents can interact by collaborating, or exchanging some information. It is usually assumed in computational social choice that every agent is able to interact with any other agent. However, this assumption looks unrealistic in many concrete situations. We propose to relax this assumption by considering that the possibility of interaction is given by a social network, represented by a graph over the agents.In this context, we study two particular problems of computational social choice: strategic voting and resource allocation of indivisible goods. The focus is on two types of interaction: collaboration and information gathering. We explore how the social network,modelingapossibilityofcollaboration or a visibility relation among the agents, can impact the resolution and the solution of voting and resource allocation problems. These questions are addressed via computational social choice by using tools from algorithmic game theory and computational complexity
Gottschal, Espen Joris. "Dynamic Thrust Allocation." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for marin teknikk, 2014. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-26848.
Kaminsky, Andrew D. "Dynamic channel allocation." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2003. http://library.nps.navy.mil/uhtbin/hyperion-image/03sep%5FKaminsky.pdf.
LE, BRIS LOIC. "Allocation de ressources radio dans les reseaux cellulaires." Paris 7, 1999. http://www.theses.fr/1999PA077136.
Kandi, Mohamed Mehdi. "Allocation de ressources élastique pour l'optimisation de requêtes." Thesis, Toulouse 3, 2019. http://www.theses.fr/2019TOU30172.
Cloud computing has become a widely used way to query databases. Today's cloud providers offer a variety of services implemented on parallel architectures. Performance targets and possible penalties in case of violation are established in advance in a contract called Service-Level Agreement (SLA). The provider's goal is to maximize its benefit while respecting the needs of tenants. Before the birth of cloud systems, several studies considered the problem of resource allocation for database querying in parallel architectures. The execution plan for each query is a graph of dependent tasks. The expression "Resource allocation" in this context often implies the placement of tasks within available resources and also their scheduling that takes into account dependencies between tasks. The main goal was to minimize query execution time and maximize the use of resources. However, this goal does not necessarily guarantee the best economic benefit for the provider in the cloud. In order to maximize the provider's benefit and meet the needs of tenants, it is important to include the economic model and SLAs in the resource allocation process. Indeed, the needs of tenants in terms of performance are different, so it would be interesting to allocate resources in a way that favors the most demanding tenants and ensure an acceptable quality of service for the least demanding tenants. In addition, in the cloud the number of assigned resources can increase/decrease according to demand (elasticity) and the monetary cost depends on the number of assigned resources, so it would be interesting to set up a mechanism to automatically choose the right moment to add or remove resources according to the load (auto-scaling). In this thesis, we are interested in designing elastic resource allocation methods for database queries in the cloud. This solution includes: (1) a static two-phase resource allocation method to ensure a good compromise between provider benefit and tenant satisfaction, while ensuring a reasonable allocation cost, (2) an SLA-driven resource reallocation to limit the impact of estimation errors on the benefit and (3) an auto-scaling method based on reinforcement learning that meet the specificities of database queries. In order to evaluate our contributions, we have implemented our methods in a simulated cloud environment and compared them with state-of-the-art methods in terms of monetary cost of the execution of queries as well as the allocation cost
Estivie, Sylvia. "Allocation de ressources multi-agents : théorie et pratique." Paris 9, 2006. https://portail.bu.dauphine.fr/fileviewer/index.php?doc=2006PA090029.
In the field of multi-agent systems, most of researches on the indivisible ressources allocation focus on the centralized problem (combinatorial auctions). To tackle this problem, we propose to use a distributed decision making coupled with negotiations between agents. The objective is to analyze the allocations reached at the end of these negotiations and more particularly with their social welfare. This study is conduced in a restricted, but very realistic, bilateral exchanges framework, where agents are selfish and rational. In the first part of the work , we present : (i) the compact representations of the preferences and the different types of utility functions, and (ii) the study of the omplexity of reaching the social welfare. Since the allocation should be both effective and equitable, in the second part of the work we focus on the egalitarianism problem in the selfish agents society. Specifically, we are concerned with different egalitarian social welfare, in respect to two points : (i) egalitarian social welfare, and (ii) envy-free. Knowing that the rational individual exchanges framework are well adopted to get the utilitarian social well fare,then two important questions should be addressed. First, up to what point these exchanges or transactions make it possible to reach or approach an egalitarian optimum? Second, what happen regarding envy? These two points will be discussed in this thesis
Pichot, Antoine. "Co-allocation de ressources distribuées : architectures, protocoles, optimisation." Phd thesis, Paris, ENST, 2008. http://pastel.archives-ouvertes.fr/pastel-00003806.
New computing applications require nowadays a physical distribution of computing resources. These geographically distributed resources belonging to different organizations must be associated logically in order to solve cooperatively a given problem or to provide a given service. The virtual infrastructure corresponding to the set of these distributed and remote resources and to the inherent underlying networking facilities is called a Grid. Present models do not enable network and other resources such as computing or storage to be co-allocated on demand, nor do they guarantee the Quality of Service. The aim of this thesis is first to provide a review of the state of the art on co-allocation. For that purpose, various environments such as Web Services distributed resources management systems, IP Multimedia Subsystem and Generalized Multi-protocol Label Switching architecture are considered. We propose extensions to existing Grid toolkits, WS, IMS and GMPLS for dynamic resource co-allocation provisioning. The suitability of each of these approaches for Grid services provisioning is investigated and compared to the other alternatives. We then analyze a WS based protocol between a global resource coordinator (Grid Scheduler) and local resources managers (local schedulers). Algorithms are proposed to model the possible interactions between the grid scheduler, the network resource manager and the local schedulers. A co-allocation algorithm is proposed to improve the efficiency as seen by the end user and the resource providers. An analytical model is proposed to predict and understand the performance; simulations are run to verify the validity of the model and the results
Dubrion, Benjamin Baudry Bernard. "Allocation et incitation intra-firme." Lyon : Université Lumière Lyon 2, 2002. http://demeter.univ-lyon2.fr:8080/sdx/theses/lyon2/2002/dubrion_b.
Boukhris, Rihab. "Allocation distribuée de ressources dans les réseaux virtuels privés." Mémoire, École de technologie supérieure, 2012. http://espace.etsmtl.ca/1050/1/BOUKHRIS_Rihab.pdf.
Toufik, Issam. "Allocation dynamique des ressources dans les futurs systèmes cellulaires." Paris, ENST, 2006. http://www.theses.fr/2006ENST0053.
In this thesis, we consider the interesting problem of channel allocation for multiuser wideband systems with Hard Fairness constraints. We first address the problem of resource allocation for single cell single antenna wideband Multiple Access Channels (MAC) under hard fairness constraints. We show that for wideband systems, with intelligently allocated resources, guaranteeing QoS for a set of users is not necessarily accompanied with a huge system performance degradation. We define the Delay-Limited capacity with a Lagrangian characterization of its boundary surface. An iterative algorithm for resource allocation to achieve a rate vector target with minimum power is proposed. We also propose different algorithms for resource allocation when orthogonal signaling is adopted with different hard fairness constraints. It is shown through numerical results that these orthogonal signaling fair algorithms achieve performances approaching that of the optimal delay limited strategy. We then extend our study to the downlink of multiple antenna multi-cellular wideband systems. We show how the additional spatial dimension affects the system performance in terms of spectral efficiency and minimum allocated channel gain. We propose different allocation and transmission techniques. We then extend our study to multi-cellular systems and show the benefit from using distributed antennas in terms of both system throughput and fairness. We also address another important issue of future wireless systems: Feed-back load. We propose different feed-back schemes, for MIMO-OFDMA systems with opportunistic beamforming
Beaujean, Christophe. "Routage et allocation de ressources dans les grands réseaux." Compiègne, 2001. http://www.theses.fr/2001COMP1342.
Abgrall, Cédric. "Allocation de ressources dans les réseaux sans fil denses." Phd thesis, Paris, Télécom ParisTech, 2010. https://pastel.hal.science/pastel-00581776.
This PhD thesis focuses on interference mitigation techniques for wireless communication networks to limit detrimental effects of in-band interference. First, we consider cooperative communication systems and study the trade-off between cooperation benefits and increased level of interference. Cooperation in wireless networks is like a crowded cocktail party with a cacophony of conversations all around. The more people repeat the same information, the more likely you understand it. However, neighbour repeaters act as interferers which harm your understanding. We propose to coordinate and adapt the activation of cooperation and the resource allocation of neighbour cells to time, frequency and space variations of communication context. Second, we propose to classify interference a destination senses on a given frequency band by differentiating three regimes of interference: noisy, intermediate and very strong. This classifier ensures an adaptive and effective processing of in-band interference adapted to time-varying nature of channel. Then, we combine this classifier with QoS constraints to derive centralized and distributed algorithms for power allocation. Both approaches aim at allocating the minimal transmit power vector while meeting QoS requirements of each user, whatever the communication scenario may be. Our simulations show how an adaptive handling of in-band interference may notably reduce the power budget without affecting transmission reliability
Abgrall, Cédric. "Allocation de ressources dans les réseaux sans fil denses." Phd thesis, Télécom ParisTech, 2010. http://pastel.archives-ouvertes.fr/pastel-00581776.
Bensaid, Bernard. "Information, incitations et mécanismes séquentiels d'allocation des ressources." Paris 1, 1989. http://www.theses.fr/1989PA010008.
Couble, Yoann pierre. "Optimisation de la gestion des ressources voie retour." Thesis, Toulouse, INPT, 2018. http://www.theses.fr/2018INPT0058.
Optimizing satellite links is a major challenge to increase satellite systems profitability. Increasing the frequency reuse is one of the most promising approaches. Reusing multiple times the same frequency enables to transmit more information on the same frequency, as long as the two or more signals do not generate too high mutual interferences. It is therefore of capital importance to control these interference impacts, be it through the use of frequency reuse scheme or through the use of advanced dynamic interference coordination techniques, where the user selection is done with the knowledge of interference levels
Houas, Heykel. "Allocation de ressources pour la transmission de données multimedia scalables." Phd thesis, Université de Cergy Pontoise, 2009. http://tel.archives-ouvertes.fr/tel-00767889.
Houas, Heykel. "Allocation de ressources pour la transmission de données multimédia scalables." Cergy-Pontoise, 2009. http://biblioweb.u-cergy.fr/theses/09CERG0430.pdf.
This thesis is dedicated to the resources allocation for the transmission of scalable multimedia data under Quality-of-Service (QoS) constraints on heterogeneous networks. We focus on wire and wireless links (DS-CDMA, OFDMA) with the transmission of images, speech over frequency and non frequency selective channels. Resources from the physical layer are addressed : channel code rates (to protect the data against the degradation of the signal-to-noise ratio SNR), modulation orders, carriers ordering (to convey the layers) and the allocated power. The aim of this report is to allocate these parameters in order to maximize the source rate of the multimedia data under targeted QoS and system payload with a perfect or partial channel knowledge. The QoS is expressed in term of perceived quality from the End To end User and in term of Bit Error Rate per Class from the scalable source encoder. In a such context, we propose some link adaptation schemes whose novelty is to enable the truncation of the data layers. Moreover, these strategies make use of the sensivity to transmission errors and the channel state information to dynamically adapt the protection of the layers (Unequal Error Protection UEP) in accordance with the QoS requirements. These procedures explore multiple resources optimization criteria : the minimization of the system payload and the maximization of the robustness to the channel estimation error. For each one, we perform the optimal allocation (bit loading) of the previous parameters that maximize the source rate while ensuring the constraints of the receiver. We show that these schemes fit to any communication system and we present the performances and compare them to the State Of The Art procedures
Aoun, Rosy. "Allocation de ressources et modèles économiques dans un environnement Cloud." Paris, ENST, 2010. http://www.theses.fr/2010ENST0075.
In the mid-1990s, the vast deployment of high-speed public data networks has motivated the externalization of private computing resources. Such an evolution is economically very attractive for enterprises for two reasons. First, data-centers externalization enables to replace costly investment in the equipment by a pay-per-use of shared resources. Second, it alleviates the operation and maintenance costs of private equipment. Cloud is the most recent evolution of distributed computing including storage and network services. In terms of resource virtualization, managing conjunctly distributed computing, storage, and network facilities remains a complex optimization problem. This problem is closely related to the design of innovative pricing strategies for Cloud Service Providers (CSPs) that act as mediators between resource owners and end-users. In practice, resource owners do not accept, for confidentiality reasons, to inform the CSP about a detailed description of their available equipment. Meanwhile, they accept to regularly provide the CSP with an abstracted view of their sharable resources. This resource abstraction introduces an additional complexity to the dynamic resource allocation problem to be solved by the CSP. In this thesis, we propose market-based resource allocation algorithms. We consider two business models depending on the fact the CSP owns or not the computing, storage and network resources. An extension to our algorithm is to make use of multicast nodes in order to manage point-to-multipoint data transfer. Another feature is to distribute storage data over multiple nodes. At the end, we propose an optimal resource abstraction algorithm
Scannavino, Aimé. "Allocation des ressources financières : contrôle monétaire et cycle de crédit." Paris 2, 1987. http://www.theses.fr/1987PA020090.
This thesis has for subject the integration of credit in economic analysis. This theme is treated first in the perspective of financial rationing phenomena, secondly through the relations between credit and economic activity; study is conducted in the economic cycle viewpoint. Consequences for monetary policy are, at last, infered
Enderle, Nicolas. "Allocation de ressources radios pour les services paquets dans l'umts." Paris, ENST, 2003. http://www.theses.fr/2003ENST0004.
In this thesis, we study scheduling policies on the umts radio interface for packet-switched services like web browsing. Moreover, we analyse the interaction between resource allocation algorithms and protocols involved in end-to-end data transmission like tcp (transmission control protocol) and rlc (radio link control). First, we model the radio resource consumption induced by active users. We then introduce a new factor : the total interference factor the radio efficiency factor. It represents the cost in radio resource per unit of throughput in order to serve a given user. Then, by formulating the resource allocation problem as an optimization problem of users' satisfaction, we present an optimal solution based on the ratio user satisfaction/radio efficiency. Thanks to these results, we build a dynamic allocation algorithm and compare our solution with existing ones from the litterature. The impact of tcp and rlc protocols is taken into account in this study
Scannavino, Aimé. "Allocation des ressources financières contrôle monétaire et cycle de crédit /." Grenoble 2 : ANRT, 1987. http://catalogue.bnf.fr/ark:/12148/cb37609734s.
Enderlé, Nicolas. "Allocation de ressources radios pour les services paquets dans l'UMTS /." Paris : École nationale supérieure des télécommunications, 2003. http://catalogue.bnf.fr/ark:/12148/cb39085229r.
Pischella, Mylène. "Allocation de ressources distribuée dans les réseaux OFDMA multi-cellulaires." Phd thesis, Paris, ENST, 2009. https://pastel.hal.science/pastel-00004978.
The thesis studies resource allocation methods, distributed per base station (BS) in multi-cellular OFDMA networks. The objective is to provide the Quality of Service (QoS) requested by each user, whatever its location in the cell. First, it investigates causal network coordination in distributed networks. Two BSs form a virtual Multiple Input, Multiple Output (MIMO) array for the users located at the border of cells. These users thus benefit from a diversity gain, and from inter-cell interference mitigation. The efficiency of the associated resource allocation method depends on the fairness of the power control objective. Thus, network coordination is used for Rate Constrained (RC) users, but not for Best Effort (BE) users, in a proposed algorithm that jointly manages both QoS objectives. The thesis next considers the more general perspective of fully distributed networks. For RC users, a resource allocation process with iterative interference-based power allocation is determined to solve the Margin Adaptive problem. It includes a distributed constraint that guarantees power control convergence. The proposed method is extended to RC users in MIMO, both when full Channel State Information is available at transmission, and when only the statistical properties of the channel are available at transmission. Finally, for BE users, the objective is to maximize the weighted sum throughput, where the weight of each user is proportional to its queue length. A subcarrier allocation method, deduced from a network-wide interference graph, and a distributed power control method are proposed for that optimization problem
Pischella, Mylène. "Allocation de ressources distribuée dans les réseaux OFDMA multi-cellulaires." Phd thesis, Télécom ParisTech, 2009. http://pastel.archives-ouvertes.fr/pastel-00004978.
Jula, Alin Narcis. "Improving locality with dynamic memory allocation." [College Station, Tex. : Texas A&M University, 2008. http://hdl.handle.net/1969.1/ETD-TAMU-2910.
Eriksson, Kristoffer. "Dynamic Resource Allocation in Wireless Networks." Thesis, Linköping University, Communication Systems, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-56776.
In this thesis we investigate different algorithms for dynamic resource allocation in wireless networks. We introduce a general framework for modeling systems whichis applicable to many scenarios. We also analyze a specific scenario with adaptivebeamforming and show how it fits into the proposed framework. We then studytwo different resource allocation problems: Quality-of-Service (QoS) constraineduser scheduling and sum-rate maximization. For user scheduling, we select some“good” set of users that is allowed to use a specific resource. We investigatedifferent algorithms with varying complexities. For the sum-rate maximizationwe find the global optimum through an algorithm that takes advantage of thestructure of the problem by reformulating it as a D.C. program, i.e., a minimizationover a difference of convex functions. We validate this approach by showing that itis more efficient than an exhaustive search at exploring the space of solutions. Thealgorithm provides a good benchmark for more suboptimal algorithms to comparewith. The framework in which we construct the algorithm, apart from being verygeneral, is also very flexible and can be used to implement other low complexitybut suboptimal algorithms.
Tjønnås, Johannes. "Nonlinear and Adaptive Dynamic Control Allocation." Doctoral thesis, Norwegian University of Science and Technology, Department of Engineering Cybernetics, 2008. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-2320.
This work addresses the control allocation problem for a nonlinear over-actuated time-varying system where parameters a¢ ne in the actuator dynamics and actuator force model may be assumed unknown. Instead of optimizing the control allocation at each time instant, a dynamic approach is considered by constructing update-laws that represent asymptotically optimal allocation search and adaptation. A previous result on uniform global asymptotic stability (UGAS) of the equilibrium of cascaded time-varying systems, is in the thesis shown to also hold for closed (not necessarily compact) sets composed by set-stable subsystems of a cascade. In view of this result, the optimal control allocation approach is studied by using Lyapunov analysis for cascaded set-stable systems, and uniform global/local asymptotic stability is guaranteed for the sets described by; the system dynamics, the optimizing allocation update-law and the adaptive update-law.
The performance of the proposed control allocation scheme is demon- strated throughout the thesis by simulations of a scaled-model ship manoeuvred at low-speed. Furthermore, the application of a yaw stabilization scheme for an automotive vehicle is presented. The stabilization strategy consists of; a high level module that deals with the vehicle motion control objective (yaw rate reference generation and tracking), a low level module that handles the braking control for each wheel (longitudinal slip control and maximal tyre road friction parameter estimation) and an intermediate level dynamic control allocation module. The control allocation module generates longitudinal slip reference for the low level brake controller and commands front wheel steering angle corrections, such that the actual torque about the yaw axis tends to the desired torque calculated by the high level module. The conditions for uniform asymptotic stability are given and the scheme has been implemented in a realistic nonlinear multi-body vehicle simulation environment. The simulation cases show that the control strategy stabilizes the vehicle in extreme manoeuvres where the nonlinear vehicle yaw dynamics otherwise become unstable in the sense of over- or understeering.
Collins, Ryan. "Dynamic Register Allocation for Network Processors." Thesis, Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/11491.
Mahesar, Fayaz Ahmed. "Dynamic Channel Allocation in GSM Network." Thesis, Blekinge Tekniska Högskola, Avdelningen för telekommunikationssystem, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-1234.
Johnson, Luke B. "Decentralized task allocation for dynamic environments." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/71458.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 93-98).
This thesis presents an overview of the design process for creating greedy decentralized task allocation algorithms and outlines the main decisions that progressed the algorithm through three different forms. The first form was called the Sequential Greedy Algorithm (SGA). This algorithm, although fast, relied on a large number of iterations to converge, which slowed convergence in decentralized environments. The second form was called the Consensus Based Bundle Algorithm (CBBA). CBBA required significantly fewer iterations than SGA but it is noted that both still rely on global synchronization mechanisms. These synchronization mechanisms end up being difficult to enforce in decentralized environments. The main result of this thesis is the creation of the Asynchronous Consensus Based Bundle Algorithm (ACBBA). ACBBA broke the global synchronous assumptions of CBBA and SGA to allow each agent more autonomy and thus provided more robustness to the task allocation solutions in these decentralized environments.
by Luke B. Johnson.
S.M.
Milner, Joseph M. (Joseph Micah). "Dynamic slot allocation with airline participation." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/11882.