Cette thèse s’intéresse aux concepts de mobilité et de gestion du spectre dans les réseaux à radio cognitive. Ainsi, nous avons proposé deux approches décentralisées basées sur les systèmes multi-agents (SMA). Nous avons, tout d’abord, intégré des agents au sein des utilisateurs secondaires (n’ayant pas de licence pour l’accès au spectre) et des utilisateurs primaires (disposant d’une licence) et nous avons défini leurs comportements au moment du handover. Notre première solution NESAM propose un mécanisme de négociation entre les agents permettant aux utilisateurs secondaires de se voir allouer une bande de spectre avec un bon rapport prix par durée d’allocation. Nous avons, par ailleurs, proposé une deuxième solution LASMA qui se base sur l’enchère combinée avec de l’apprentissage pour assurer une gestion efficace du spectre ainsi qu’une gestion de la mobilité des utilisateurs à radio cognitive. Nos algorithmes prennent en compte les préférences des utilisateurs, comme la fréquence spectrale, le prix et la durée ainsi que les contraintes de l’environnement spectral telles que les bandes de fréquences disponibles. Nos propositions assurent une exploitation importante des ressources spectrales tout en diminuant le nombre de handovers spectraux. De plus, nos algorithmes offrent un handover spectral transparent et sans interruption lors des déplacements des utilisateurs. Nous avons prouvé également que nos solutions permettent de satisfaire les besoins des utilisateurs et d’améliorer leur utilité / In this thesis, we are interested in mobile cognitive radio networks while ensuring an efficient spectrum sharing and seamless handover at the same time. Hence, we propose two decentralized approaches based on multi-agents systems. We first deployed agents on each primary (licensed) and secondary (unlicensed cognitive radio) users, respectively. Besides, we define agents’ behaviors during the handover process.Our proposal NESAM defines a novel negotiation mechanism between agents to allow secondary users assigning the appropriate spectrum band giving a good price for the use duration. We have also proposed a second solution LASMA using the learning based auctions. Our algorithms take into account users’ requirements such as spectrum frequency, price and duration as well as environment’s constraints such as available resources.Our proposals improve the overall spectrum utilization and minimize the number of spectrum handovers when users move from one network to another one. This proves that our algorithms ensure efficient spectrum allocation and enable seamless handover during user’s mobility. Besides, we proved that our approaches guarantee users’ satisfaction and improve their utility

This diploma thesis is focused on reverse e-auctions and their utilization in construction companies. In theoretical part of the work are terms of purchase and auction defined and described process of e-auction. The practical part analyzes situations in construction companies by questionnaire survey and case study. Consequently recommendations for provision of carefree process of e-auction are proposed.

This thesis is focused on analysis of the use of electronic reverse auctions in the construction industry in Slovakia. The theoretical part provides the basic concepts, types and participants of electronic auctions. There are also analysed in detail the electronic reverse auctions as an important tool for procurement processes in the construction industry. The practical part deals with the analysis and subsequent recommendation for the construction sector - through a questionnaire survey.

The goal of the PhD thesis is to investigate the role of behavioural economics considerations for the performance of conservation auctions. The findings of the three scientific articles suggest that behavioural economics considerations like social (distributional) preferences and reference-dependent preferences may affect the attractiveness and economic performance of conservation auctions, respectively. The results of the first and second articles are based on laboratory experiments conducted with university students, in Germany. The third article implements a field experiment to measure farmers’ preferences over Payments for Ecosystem Services (PES) allocation mechanisms and the role of fairness therein, in the context of agrobiodiversity loss in Benin.

La densification de réseau à l'aide de petites cellules massivement déployées sur les zones macro-cellules, représente une solution prometteuse pour les réseaux mobiles 5G avenir pour faire face à l'augmentation du trafic mobile. Afin de simplifier la gestion de l'hétérogène du réseau d'accès radio (Radio Access Network RAN) qui résulte du déploiement massif de petites cellules, des recherches récentes et des études industrielles ont favorisé la conception de nouvelles architectures de RAN centralisés appelés comme Cloud-RAN (C-RAN), ou RAN virtuel (V-RAN), en incorporant les avantages du cloud computing et Network Functions Virtualization (NFV). Le projet de DynaRoC vise l'élaboration d'un cadre théorique de l'orchestration de ressources pour les C-RAN et dériver les limites de performance fondamentaux ainsi que les arbitrages entre les différents paramètres du système, et la conception de mécanismes d'orchestration de ressources dynamiques sur la base des conclusions théoriques à atteindre un équilibre de performance souhaité, en tenant compte des différents défis de conception. Le doctorant va étudier les mécanismes d'optimisation des ressources novatrices pour favoriser le déploiement de C-RAN, améliorer leur performance exploitant la technologie Network Functions Virtualization / 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

This study investigates Game theory including economic theories related to agricultural production. Model creation simulating economical system is built upon theoretic starting points. Commodity production is simulated using game theory with searching for Nash equilibria. Commodity demand function is grounded on concept of Cournot game. System includes land trading based on sealed-bid auctions with second-price. This model is using external Gambit software which is freeware library for game theory computations. Model evaluation is located in Experiments section where model structure and truthfulness is tested.

We study two classes of problems within Algorithmic Economics: revenue guarantees of simple mechanisms, and social welfare guarantees of auctions. We develop new structural and algorithmic tools for addressing these problems, and obtain the following results: In the 𝑘-unit model, four canonical mechanisms can be classified as: (i) the discriminating group, including Myerson Auction and Sequential Posted-Pricing, and (ii) the anonymous group, including Anonymous Reserve and Anonymous Pricing. We prove that any two mechanisms from the same group have an asymptotically tight revenue gap of 1 + θ(1 /√𝑘), while any two mechanisms from the different groups have an asymptotically tight revenue gap of θ(log 𝑘). In the single-item model, we prove a nearly-tight sample complexity of Anonymous Reserve for every value distribution family investigated in the literature: [0, 1]-bounded, [1, 𝐻]-bounded, regular, and monotone hazard rate (MHR). Remarkably, the setting-specific sample complexity poly(𝜖⁻¹) depends on the precision 𝜖 ∈ (0, 1), but not on the number of bidders 𝑛 ≥ 1. Further, in the two bounded-support settings, our algorithm allows correlated value distributions. These are in sharp contrast to the previous (nearly-tight) sample complexity results on Myerson Auction. In the single-item model, we prove that the tight Price of Anarchy/Stability for First Price Auctions are both PoA = PoS = 1 - 1/𝜖² ≈ 0.8647.

No description available.

In Paper [I] we use data on Swedish public procurement auctions for internal regularcleaning service contracts to provide novel empirical evidence regarding green publicprocurement (GPP) and its effect on the potential suppliers’ decision to submit a bid andtheir probability of being qualified for supplier selection. We find only a weak effect onsupplier behavior which suggests that GPP does not live up to its political expectations.However, several environmental criteria appear to be associated with increased complexity,as indicated by the reduced probability of a bid being qualified in the postqualificationprocess. As such, GPP appears to have limited or no potential to function as an environmentalpolicy instrument. In Paper [II] the observation is made that empirical evaluations of the effect of policiestransmitted through public procurements on bid sizes are made using linear regressionsor by more involved non-linear structural models. The aspiration is typically to determinea marginal effect. Here, I compare marginal effects generated under both types ofspecifications. I study how a political initiative to make firms less environmentally damagingimplemented through public procurement influences Swedish firms’ behavior. Thecollected evidence brings about a statistically as well as economically significant effect onfirms’ bids and costs. Paper [III] embarks by noting that auction theory suggests that as the number of bidders(competition) increases, the sizes of the participants’ bids decrease. An issue in theempirical literature on auctions is which measurement(s) of competition to use. Utilizinga dataset on public procurements containing measurements on both the actual and potentialnumber of bidders I find that a workhorse model of public procurements is bestfitted to data using only actual bidders as measurement for competition. Acknowledgingthat all measurements of competition may be erroneous, I propose an instrumental variableestimator that (given my data) brings about a competition effect bounded by thosegenerated by specifications using the actual and potential number of bidders, respectively.Also, some asymptotic results are provided for non-linear least squares estimatorsobtained from a dependent variable transformation model. Paper [VI] introduces a novel method to measure bidders’ costs (valuations) in descending(ascending) auctions. Based on two bounded rationality constraints bidders’costs (valuations) are given an imperfect measurements interpretation robust to behavioraldeviations from traditional rationality assumptions. Theory provides no guidanceas to the shape of the cost (valuation) distributions while empirical evidence suggeststhem to be positively skew. Consequently, a flexible distribution is employed in an imperfectmeasurements framework. An illustration of the proposed method on Swedishpublic procurement data is provided along with a comparison to a traditional BayesianNash Equilibrium approach.

Infrastructure—communications, energy, transport, waste, and water networks—is critical for economic activity and social well-being. Practitioners, politicians, and economists advocate high levels of investment in infrastructure under the rubric of 'planning for growth' (or the 'push' paradigm). This paradigm relies on complex public-private arrangements in the name of public interest. These seemingly reasonable arrangements are, however, not delivering their promise. Evidence shows that the needs of infrastructure users in rich and poor countries are not being met, many private providers of infrastructure earn rich returns, assets are rarely built in time or on budget, and there is tremendous waste in the operation of many infrastructure industries. No other sector could survive the profligacy and slack common in infrastructure. I distil the following primary propositions of the accepted wisdom, which is inspired by mainstream economics: First, infrastructure assets necessarily entail high sunk costs and large economies of scale. Consequently, assets last for very long periods of time, and they cannot be readily moved. Second, infrastructure outputs are homogeneous. Third, one network fits all users (large and small). Fourth, infrastructure users, even large ones, are likely to have weak bargaining power in procurement of infrastructure outputs. I challenge these four propositions of the conventional wisdom by putting forward alternative hypotheses. First, instead of being monolithic and costly, infrastructures can be assembled (and disassembled) as flexible modules for specific users in specific places. Drawing on option pricing theory in quantitative finance, I recast infrastructures as 'portfolios of real options'. Second, infrastructure outputs are, in fact, heterogeneous and differentiated services. Third, one infrastructure network cannot fit all users, either today or in the future. Users are remarkably heterogeneous, not only in terms of unique user preferences but also in terms of spatial location. Infrastructure networks need to evolve in tandem with user needs or risk spatial, temporal, and relational obsolescence. Finally, users, large and small, are adept at exerting strong bargaining power in procuring infrastructure both prior to and after rendering durable and immobile investments. Users also strategically deploy intermediaries, e.g. futures and Over-the-Counter (OTC) exchanges, and real estate developers, to negotiate private contracts for infrastructure services. These findings are supported by two case studies. The first case study details the process by which ThyssenKrupp, a large steel company, bargained for its infrastructure by locating to a manufacturing site in the U.S. The second case study focuses on residents of Lavasa, one of the largest property developments in India. Here, small users of infrastructure exert strong bargaining power with the aid of intermediaries—the real estate developer and the property asset manager. New departures in infrastructure provision are urgently needed at a practical level. Poor investments rendered today—particularly if costly, inflexible, and durable—will suffocate tomorrow’s possibilities. The spatial, temporal, and relational approach proposed in this dissertation begins to offer an alternative account of how tomorrow can be modularly shaped.