Dissertations / Theses on the topic 'Resource allocation strategies'

The use of precision automated electronic balances has allowed remote quantification of instantaneous and long term body mass changes in breeding swallows, Hirundo rustica. By means of observation, experiment and optimality modelling, the extent of mass changes during incubation and nestling rearing are described, and the fitness consequences of mass changes discussed. An understanding of the causes and consequences of mass changes in swallows is developed from laboratory investigations of short term mass changes in canaries Serinus canarius, and from carcass analysis of breeding sand martins R. riparia, and swallows. Parent: offspring resource allocation was investigated during incubation in swallows. A model is developed which assumes that fitness is maximised in individuals which spend most time on the nest as a result of maximising the difference between net gain while foraging and clutch reheating costs, measured in units of energy. The model is tested, and the most frequently observed inattentive period proves, to be similar to that predicted to be the most energetically profitable. The early decline in swallow body mass during nestling rearing is likely to represent a 'programmed' anorexia in females during the brooding phase, whereby mass loss is beneficial in reducing flight costs and releasing energy available for work. After termination of brooding, however, mass losses were associated with rapid feeding rates to the brood for both sexes, and were judged to be potentially costly in terms of adult survival. (ii) By concurrent monitoring of resources for parents and offspring, investment in self-maintenance relative to investment in offspring is calculated, and the results interpreted in the wider context of lifehistory tactics and parental investment theories. Both sexes of swallow invested more in 'self' relative to 'offspring' when food was scarce or when feeding broods of small metabolic mass. Females appeared to risk their body mass falling to lower levels than that of their mates when feeding conditions were poor. overall, the study showed that the costs and benefits of mass changes in swallows differed according to the stage of the breeding cycle, and that detailed knowledge of the causes of mass changes allows insight into the evolution of reproductive strategies of birds of both sexes in relation to individual quality and resource availability.

Avec les préoccupations environnementales croissantes liées aux émissions de carbone et la chute rapide des prix des batteries, la part de marché des véhicules électriques (EV) augmente rapidement. Le nombre croissant de EV ainsi que les progrès sans précédent dans la capacité de la batterie et de la technologie entraîne une augmentation drastique de la demande totale d'énergie destinée aux véhicules électriques. Cette forte demande de charge rend complexe le problème de planification de la charge. Même en prenant avantage de la propriété reportable des demandes de charge et d'une planification adéquate, la demande globale pourrait dépasser le taux de charge tolérable des stations, étant donné les contraintes physiques des dispositifs de charge et des transformateurs. Le principal défi est la nécessité de concevoir des solutions en ligne puisque, dans la pratique, l'ordonnanceur ne dispose d'aucune information sur les arrivées futures d'EV. Cette thèse étudie le problème d'ordonnancement des EV en ligne et fournit trois contributions principales. Premièrement, nous démontrons que le problème classique de la programmation en ligne des tâches sensibles aux échéances avec des valeurs partielles est similaire au problème d'ordonnancement EV et étudions l'extension de la programmation des charges EV en prenant en compte de la limite de traitement des travaux. Le problème réside dans la catégorie des problèmes d'ordonnancement en ligne couplés dans le temps sans disponibilité d'informations futures. Le premier algorithme proposé est déterministe, tandis que le second est randomisé et bénéficie d'une complexité de calcul plus faible. Deuxièmement, nous formulons un problème de maximisation du bien-être social pour la planification de la charge des EV avec une contrainte de capacité de charge. Nous avons conçu des algorithmes d'ordonnancement de charge qui non seulement fonctionnent dans un scénario en ligne, mais aussi qui répondent aux deux principaux défis suivants : (i) fournir un engagement à l'arrivée ; (ii) garantir la résistance aux stratégies (de groupe). Des simulations approfondies utilisant des traces réelles démontrent l'efficacité de nos algorithmes d'ordonnancement en ligne par rapport à la solution hors-ligne optimale non-engagée. La troisième contribution concerne la planification en ligne des véhicules électriques dans un réseau de recharge adaptatif (ACN) avec des contraintes de pics locaux et globaux. Nous avons conçu un algorithme d'ordonnancement primal-dual de faible complexité qui atteint un rapport d'approximation borné. Des résultats expérimentaux détaillés basés sur des traces montrent que les performances des algorithmes en ligne proposés sont proches de l'optimum hors ligne et surpassent les solutions existantes<br>With the increased environmental concerns related to carbon emission, and rapid drop in battery prices (e.g., 35% drop in 2017), the market share of Electric Vehicles (EVs) is rapidly growing. The growing number of EVs along with the unprecedented advances in battery capacity and technology results in drastic increase in the total energy demand of EVs. This large charging demand makes the EV charging scheduling problem challenging. The critical challenge is the need for online solution design since in practical scenario the scheduler has no information of future arrivals of EVs in a time-coupled underlying problem. This thesis studies online EV scheduling problem and provides three main contributions. First, we demonstrate that the classical problem of online scheduling of deadlinesensitive jobs with partial values is similar to the EV scheduling problem and study the extension to EV charging scheduling by taking into account the processing rate limit of jobs as an additional constraint to the original problem. The problem lies in the category of time-coupled online scheduling problems without availability of future information. Using competitive ratio, as a well-established performance metric, two online algorithms, both of which are shown to be (2 − 1/U)-competitive are proposed, where U is the maximum scarcity level, a parameter that indicates demand-to-supply ratio. Second, we formulate a social welfare maximization problem for EV charging scheduling with charging capacity constraint. We devise charging scheduling algorithms that not only work in online scenario, but also they address the following two key challenges: (i) to provide on-arrival commitment; respecting the capacity constraint may hinder fulfilling charging requirement of deadline-constrained EVs entirely. Therefore, committing a guaranteed charging amount upon arrival of each EV is highly required; (ii) to guarantee (group)-strategy-proofness as a salient feature to promote EVs to reveal their true type and do not collude with other EVs. Third, we tackle online scheduling of EVs in an adaptive charging network (ACN) with local and global peak constraints. Two alternatives in resource-limited scenarios are to maximize the social welfare by partially charging the EVs (fractional model) or selecting a subset of EVs and fully charge them (integral model). For the fractional model, both offline and online algorithms are devised. We prove that the offline algorithm is optimal. We prove the online algorithm achieves a competitive ratio of 2. The integral model, however, is more challenging since the underlying problem is NP-hard due to 0/1 selection criteria of EVs. Hence, efficient solution design is challenging even in offline setting. We devise a low-complexity primal-dual scheduling algorithm that achieves a bounded approximation ratio. Built upon the offline approximate algorithm, we propose an online algorithm and analyze its competitive ratio in special cases

The relationship between food security and sustainable land use is considered to be of the uttermost importance to increase yields without having to increase the agricultural land area Over which crops are grown. In the present study nitrogen concentration (25 and 85 kg/hal and planting density (6.7, 10 and 25 plants/m') were investigated for their effect on the plant Physiology and seed yield of kale (Brassica aleracea), to determine if the fruit (pod) yield could be manipulated agronomically. Nitrogen did not significantly affect seed yield and it is therefore recommended that the lower concentration be used commercially. Conversely Planting density did have a significant effect with increases in seed yield observed at the highest planting density of 25 plants/m', therefore this high planting density would be recommended commercially to maximise area efficiency, highlighting that simple agronomic changes are capable of increasing crop yields over a set area.

L'ultra large bande (UWB) est une nouvelle technologie à fort potentiel pour les futurs réseaux personnels WPAN (wireless personal area networks) à très haut débit et faible portée. L'objectif de cette thèse est de proposer un nouveau système UWB, de type LP-OFDM (linear precoded orthogonal frequency division multiplexing) pour les applications WPAN, visant à améliorer la solution MB-OFDM (multiband OFDM), supportée par l'Alliance WiMedia.<br />Dans un premier temps, une étude analytique est menée sur l'apport de la composante de précodage au système UWB, cette composante se réduisant en pratique à une simple addition d'une matrice d'étalement fréquentiel. La fonction de précodage est ensuite optimisée et différentes stratégies d'allocation dynamique des ressources sont étudiées. En considérant une approche classique tenant compte du taux d'erreur symbole (TES) ainsi qu'une nouvelle approche tenant compte du taux d'erreur binaire (TEB) moyen, différents algorithmes d'allocation dynamique visant à maximiser la portée ou le débit du système, ou à minimiser le TEB moyen du système, sont proposés. Les résultats analytiques montrent l'avantage d'utiliser une composante de précodage pour les applications UWB dont le canal est très sélectif en fréquence.<br />Dans un second temps, une étude système complémentaire à l'étude analytique est réalisée pour le système LP-OFDM UWB. Une composante MIMO est ajoutée au système, d'une part pour augmenter la portée du système à bas et moyen débit, et d'autre part pour augmenter le débit du système qui peut atteindre dans ce cas 1 gigabit/s. Les résultats de simulation sur le système proposé montrent que ce système est plus performant que le système MB-OFDM pour les débits déjà proposés dans la norme, et qu'il offre un débit deux fois plus important que ceux de la norme avec même une meilleure performance en terme de TEB.

"We are in an era of big data, sensors, and monitoring technology. One consequence of this technology is the continuous generation of massive volumes of streaming data. To support this, stream processing systems have emerged. These systems must produce results while meeting near-real time response obligations. However, computation intensive processing on high velocity streams is challenging. Stream arrival rates are often unpredictable and can fluctuate. This can cause systems to not always be able to process all incoming data within their required response time.Yet inherently some results may be much more significant than others. The delay or complete neglect of producing certain highly significant results could result in catastrophic consequences. Unfortunately, this critical problem of targeted prioritized processing in overloaded environments remains largely unaddressed to date. In this talk, I will describe four key challenges that my dissertation successfully tackled. First, I address the problem of optimally processing the most significant tuples identified by the user at compile-time before less critical ones. Second, I propose a new aggregate operator that increases the accuracy of aggregate results produced for TP systems. Third, I address the problem of identifying and pulling forward significant tuples at run-time via dynamic determinants. Fourth, I design multi-input operators, such as the join operator, which produce multi-stream results in significance order. My experimental studies explore a rich diversity of workloads, queries, and data sets, including real data streams. The results substantiate that my approaches are a significant improvement over the state-of-the-art approaches."

Dynamic Spectrum Access (DSA) and multi-input multi-output (MIMO) communications are among the most promising solutions to address the ever-increasing wireless demand. Cognitive radio (CR) is the enabling technology for DSA. In this dissertation, we propose several resource allocation strategies for multiuser and cooperative MIMO communications in the context of DSA/CR systems and wireless sensor networks (WSNs). First, to maximize the Cognitive MIMO (CMIMO) network throughput, we develop a low-complexity distributed algorithm that configures the transmit antenna radiation directions and allocates power to all data streams over both frequency and space/antenna dimensions. We formulate the joint power, spectrum allocation, and MIMO beamforming problem as a noncooperative game. We prove that the game always admits at least one Nash Equilibrium (NE). To improve the efficiency of this NE (i.e., network throughput), we derive user-dependent pricing policies that force MIMO transmitters to steer their beams away from nearby unintended receivers. Second, we propose beamforming games (with and without pricing policies) that jointly improve the power and spectrum efficiency while meeting various rate demands. We derive sufficient conditions under which a given rate-demand profile can be supported. To account for user fairness, we develop a channel assignment and power allocation mechanism based on the Nash Bargaining solution. The proposed scheme allows CMIMO links to first propose their rate demands, and then cooperate and bargain in the process of determining their channel assignment, power allocation, and "precoding" matrices. In the context of WSNs where energy efficiency is a key design metric, we propose a cooperative MIMO framework. The framework partitions a WSN into various clusters in which several single-antenna sensors cooperate and form a virtual MIMO node so as to conserve power through harvesting MIMO's diversity gain. Extensive simulations show that our proposed schemes achieve significant throughput and energy efficiency improvement compared with state-of-the-art designs.

Resource allocation strategies, including power control, rate adaptation, and dynamic spectrum access, have been the keys to improving the performance of dynamic (mobile) wireless networks. In this dissertation, we propose several resource optimization schemes for various wireless network architectures, with the goal of maximizing the system throughput and/or minimizing the total energy consumption. These schemes are integrated into the design of distributed medium-access control (MAC) protocols. We propose a game theoretic power control scheme for single-channel ad-hoc networks, and design an efficient MAC protocol, called GMAC, that implements such a scheme in a distributed fashion. GMAC allows for multiple potential transmitters to contend for the channel through an admission phase that these transmitters to determine their appropriate transmission powers. Successful contenders proceed concurrently following the admission phase. We then study the operation of spectrum-agile (cognitive) radios in multi-channel, multi-hop wireless network setting. Two principal cases are considered: exclusive-occupancy and interference-based channel models. For the case of exclusive-occupancy channel models, we design a MAC protocol that exploits the "dual receive" capabilities of the radios to maximize the network throughput. We then propose a cross-layer framework for joint adaptive load/medium access controls. Under this framework, the traffic loads of individual node are adapted based on local MAC parameters. For the case of interference-based channel models, when system throughput is the primary performance metric, we apply "price-based" iterative water-filling (PIWF) algorithms for resource allocation. When energy consumption is the primary metric, we propose a selfish update algorithm and an incentive-based update algorithm for minimizing the power consumption while satisfying the rate and power mask requirements. These algorithms are implemented by having nodes repeatedly negotiate their best power/spectrum to reach a good Nash Equilibrium. An efficient multi-channel MAC protocol is proposed to facilitate the radio negotiation and convergence phase. Simulation results indicate that our proposed protocols achieve significant throughput/energy improvements over existing protocols.

Thesis (S.M.)--Massachusetts Institute of Technology, System Design & Management Program, February 2004.<br>Includes bibliographical references (p. 69-72).<br>This is a study into the allocation of resources in the early stages of research in a small commercial entity that develops innovative technologies. The premise is that resource allocation must focus on the implementation of the technology from a broad, end-to-end, systems viewpoint rather than purely on the inventive or scientific research. Only by understanding and addressing issues early in a development process can technology be efficiently developed. This thesis examines in depth the approach to the development of technologies taken by eight small innovative research companies in the New England Area. These companies all received funding through the government's Small Business Innovative Research program. Half of the companies received additional funding from external entities and qualified for Fast Track funding from the Department of Defense. The study was conducted by means of a questionnaire and in person interviews to identify how companies identify, evaluate and allocate resources to challenges. The strategies that were followed, problems encountered, collaborations with other entities and the outcomes of their programs were examined. This process set up a natural experiment between companies that received Fast Track and thus external funding on the basis of augmented external communication. The main conclusions of the research are that the Fast Track program, for the small sample studied here, did not influence the processes followed by the companies. Rather the long-term strategies of the companies dictated how they dealt with adversity. Moreover, in contradiction to previous studies that examined these same companies immediately after the SBIR work was completed, the fast-track companies showed no greater commercialization<br>(cont.) success than the comparison companies. The diminished differentiator of the Fast Track program can be attributed to a) the great deal of uncertainty that is inherent with applications research and b) the short time and limited funding of the SBIR program, which in itself limits the probability of success independent of the Fast-Track mechanism.<br>by Jacob v.R. Pretorius.<br>S.M.

This thesis concerns communication across channels with multiple inputs and multiple outputs. Specifically, we consider the closed-loop scenario in which knowledge of the state of the multiple-input multiple-output (MIMO) channel is available at the transmitter. We show how this knowledge can be exploited to optimize performance, as measured by the zero-outage capacity, which is the capacity corresponding to zero outage probability. On at-fading channels, a closed-loop transmitter allocates different powers and rates to the multiple channel inputs so as to maximize zero-outage capacity. Frequency-selective fading channels call for a combination of orthogonal-frequency-division multiplexing (OFDM) and MIMO known as MIMO-OFDM. This exacerbates the allocation problem because it multiplies the number of allocation dimensions by the number of OFDM tones. Fortunately, this thesis demonstrates that simple allocations are sufficient to approach the zero-outage capacity. These simple strategies exploit the tendency for random MIMO channels to behave deterministically as the number of inputs becomes large.

Ces dernières années, le développement des réseaux de communication indoor et outdoor et l'augmentation du nombre d'applications conduisent à un besoin toujours croissant de transmission de données à haut débit. Parmi les nombreuses technologies concurrentes, les communications par courant porteur en ligne (CPL) ont leur place en raison des infrastructures déjà disponibles. La motivation principale de cette thèse est d'augmenter le débit et la robustesse des systèmes CPL à porteuses multiples afin qu'ils puissent être utilisés efficacement dans les réseaux domestiques et pour la domotique. Le thème de ce travail de recherche est d'explorer différentes approches de modulation et de codage de canal en liaison avec plusieurs schémas d'allocation et d'optimisation des ressources. L'objectif est ici d'améliorer les capacités des CPL et d'être concurrent face aux autres solutions de communication à haut débit et de faire face efficacement aux inconvénients inhérents au réseau d'alimentation. Un certain nombre de stratégies d'allocation des ressources et d'optimisation sont étudiées pour améliorer les performances globales des systèmes CPL. La performance d'un système de communication est généralement mesurée en termes de débit, de marge de bruit et de taux d'erreur binaire (TEB) de la liaison. La maximisation de débit (RM) est étudiée pour les systèmes OFDM (en anglais orthogonal frequency division multiplexing) et LP-OFDM (en anglais linear precoded OFDM) sous la contrainte de densité spectrale de puissance (DSP). Deux contraintes différentes de taux d'erreur ont été appliquées au problème RM. La première contrainte est la contrainte de TEB crête où toutes les sous-porteuses ou séquences de précodage doivent respecter le TEB cible. Avec la deuxième contrainte, contrainte de TEB moyen, différentes sous-porteuses ou séquences de précodage sont affectées par des valeurs différentes de TEB et une contrainte de TEB moyen est imposée sur le symbole complet OFDM ou LP-OFDM. Les algorithmes d'allocation sont également proposés en prenant en compte les gains de codage de canal dans le processus d'allocation des ressources. En outre, un nouveau schéma de minimisation de TEB moyen est introduit qui minimise le TEB moyen de systèmes pour un débit donné et un masque imposé de DSP. Pour l'allocation des ressources dans un système à porteuses multiples, il est généralement supposé que l'état du canal (CSI) est parfaitement connu par l'émetteur. En réalité, les informations de CSI disponibles au point d'émission sont imparfaites. Aussi, nous avons également étudié des schémas d'allocation des ressources dans le cas de systèmes OFDM et LP-OFDM en prenant compte, et de manière efficace, les impacts des estimations bruitées. Plusieurs chaînes de communication sont aussi développées pour les systèmes OFDM et LP-OFDM.

Thesis (M.S.)--Massachusetts Institute of Technology, Sloan School of Management, 1990.<br>Title as it appears in the M.I.T. Graduate List, June 1990: Performance analysis and optimization queing [sic] networks in a dynamic environment.<br>Includes bibliographical references (leaf 162).<br>by Douglas Davidson Zone.<br>M.S.

Thesis (Ph.D.)--RAND Graduate School, 2009.<br>"This document was submitted as a dissertation in June 2009 in partial fulfillment of the requirements of the doctoral degree in public policy analysis at the Pardee RAND Graduate School. The faculty committee that supervised and approved the dissertation consisted of Gregory F. Treverton (Chair), Lynn E. Davis, David E. Mosher, and Walter L. Perry. Professor Kathryn Blackmond Laskey (George Mason University) was the external reader. Financial support for this dissertation was provided by RAND's National Defense Research Institute"--Cover. Title from title screen (viewed on Aug. 24, 2009). Includes bibliographical references: p. 100-105.

Hoy en día existen varias tecnologías que coexisten en una misma zona formando un sistema heterogéneo. Además, este hecho se espera que se vuelva más acentuado con todas las nuevas tecnologías que se están estandarizando actualmente. Hasta ahora, generalmente son los usuarios los que eligen la tecnología a la que se van a conectar, ya sea configurando sus terminales o usando terminales distintos. Sin embargo, esta solución es incapaz de aprovechar al máximo todos los recursos. Para ello es necesario un nuevo conjunto de estrategias. Estas estrategias deben gestionar los recursos radioeléctricos conjuntamente y asegurar la satisfacción de la calidad de servicio de los usuarios. Siguiendo esta idea, esta Tesis propone dos nuevos algoritmos. El primero es un algoritmo de asignación dinámica de recusos conjunto (JDRA) capaz de asignar recursos a usuarios y de distribuir usuarios entre tecnologías al mismo tiempo. El algoritmo está formulado en términos de un problema de optimización multi-objetivo que se resuelve usando redes neuronales de Hopfield (HNNs). Las HNNs son interesantes ya que se supone que pueden alcanzar soluciones sub-óptimas en cortos periodos de tiempo. Sin embargo, implementaciones reales de las HNNs en ordenadores pierden esta rápida respuesta. Por ello, en esta Tesis se analizan las causas y se estudian posibles mejoras. El segundo algoritmo es un algoritmo de control de admisión conjunto (JCAC) que admite y rechaza usuarios teniendo en cuenta todas las tecnologías al mismo tiempo. La principal diferencia con otros algorimos propuestos es que éstos últimos toman las dicisiones de admisión en cada tecnología por separado. Por ello, se necesita de algún mecanismo para seleccionar la tecnología a la que los usuarios se van a conectar. Por el contrario, la técnica propuesta en esta Tesis es capaz de tomar decisiones en todo el sistema heterogéneo. Por lo tanto, los usuarios no se enlazan con ninguna tecnología antes de ser admitidos.<br>Calabuig Soler, D. (2010). Common Radio Resource Management Strategies for Quality of Service Support in Heterogeneous Wireless Networks [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/7348<br>Palancia

The HIV/AIDS epidemic and the COVID-19 pandemic have ruined many people's lives. Antiretroviral therapy (ART) has controlled the HIV/AIDS epidemic and COVID-19 vaccine is expected to ease confusion caused by the pandemic. However, the supply of health-resource falls far short of the demand in resource-constrained countries; thus, decision-making about resource allocation should be discussed. Botswana, as a resource-constrained country with a high prevalence of HIV, needs to construct its own framework for ART allocation. We propose an equitable framework for ART and COVID-19 vaccine allocation in Botswana based upon the egalitarian principle, which provides each individual has an equal chance of receiving them. We use a spatial mathematical model of treatment accessibility with an equity objective function, and sequential quadratic programming is used to address the nonlinear programming model. Considering Botswana's current health infrastructure, our strategy brings the most equal health outcomes. However, the disparity of accessibility still exists between rural and urban areas even from our equitable strategy. We present proposals that can increase the accessibility of rural areas using sensitivity analysis. Our work can be applied to different contexts, especially in sub-Saharan Africa.

This dissertation addresses five fundamental resource allocation problems on networks, all of which have applications to support Homeland Security or industry challenges. In the first application, we model and solve the strategic problem of minimizing the expected loss inflicted by a hostile terrorist organization. An appropriate allocation of certain capability-related, intent-related, vulnerability-related, and consequence-related resources is used to reduce the probabilities of success in the respective attack-related actions, and to ameliorate losses in case of a successful attack. Given the disparate nature of prioritizing capital and material investments by federal, state, local, and private agencies to combat terrorism, our model and accompanying solution procedure represent an innovative, comprehensive, and quantitative approach to coordinate resource allocations from various agencies across the breadth of domains that deal with preventing attacks and mitigating their consequences. Adopting a nested event tree optimization framework, we present a novel formulation for the problem as a specially structured nonconvex factorable program, and develop two branch-and-bound schemes based respectively on utilizing a convex nonlinear relaxation and a linear outer-approximation, both of which are proven to converge to a global optimal solution. We also investigate a fundamental special-case variant for each of these schemes, and design an alternative direct mixed-integer programming model representation for this scenario. Several range reduction, partitioning, and branching strategies are proposed, and extensive computational results are presented to study the efficacy of different compositions of these algorithmic ingredients, including comparisons with the commercial software BARON. The developed set of algorithmic implementation strategies and enhancements are shown to outperform BARON over a set of simulated test instances, where the best proposed methodology produces an average optimality gap of 0.35% (compared to 4.29% for BARON) and reduces the required computational effort by a factor of 33. A sensitivity analysis is also conducted to explore the effect of certain key model parameters, whereupon we demonstrate that the prescribed algorithm can attain significantly tighter optimality gaps with only a near-linear corresponding increase in computational effort. In addition to enabling effective comprehensive resource allocations, this research permits coordinating agencies to conduct quantitative what-if studies on the impact of alternative resourcing priorities. The second application is motivated by the author's experience with the U.S. Army during a tour in Iraq, during which combined operations involving U.S. Army, Iraqi Army, and Iraqi Police forces sought to interdict the transport of selected materials used for the manufacture of specialized types of Improvised Explosive Devices, as well as to interdict the distribution of assembled devices to operatives in the field. In this application, we model and solve the problem of minimizing the maximum flow through a network from a given source node to a terminus node, integrating different forms of superadditive synergy with respect to the effect of resources applied to the arcs in the network. Herein, the superadditive synergy reflects the additional effectiveness of forces conducting combined operations, vis-à-vis unilateral efforts. We examine linear, concave, and general nonconcave superadditive synergistic relationships between resources, and accordingly develop and test effective solution procedures for the underlying nonlinear programs. For the linear case, we formulate an alternative model representation via Fourier-Motzkin elimination that reduces average computational effort by over 40% on a set of randomly generated test instances. This test is followed by extensive analyses of instance parameters to determine their effect on the levels of synergy attained using different specified metrics. For the case of concave synergy relationships, which yields a convex program, we design an inner-linearization procedure that attains solutions on average within 3% of optimality with a reduction in computational effort by a factor of 18 in comparison with the commercial codes SBB and BARON for small- and medium-sized problems; and outperforms these softwares on large-sized problems, where both solvers failed to attain an optimal solution (and often failed to detect a feasible solution) within 1800 CPU seconds. Examining a general nonlinear synergy relationship, we develop solution methods based on outer-linearizations, inner-linearizations, and mixed-integer approximations, and compare these against the commercial software BARON. Considering increased granularities for the outer-linearization and mixed-integer approximations, as well as different implementation variants for both these approaches, we conduct extensive computational experiments to reveal that, whereas both these techniques perform comparably with respect to BARON on small-sized problems, they significantly improve upon the performance for medium- and large-sized problems. Our superlative procedure reduces the computational effort by a factor of 461 for the subset of test problems for which the commercial global optimization software BARON could identify a feasible solution, while also achieving solutions of objective value 0.20% better than BARON. The third application is likewise motivated by the author's military experience in Iraq, both from several instances involving coalition forces attempting to interdict the transport of a kidnapping victim by a sectarian militia as well as, from the opposite perspective, instances involving coalition forces transporting detainees between interment facilities. For this application, we examine the network interdiction problem of minimizing the maximum probability of evasion by an entity traversing a network from a given source to a designated terminus, while incorporating novel forms of superadditive synergy between resources applied to arcs in the network. Our formulations examine either linear or concave (nonlinear) synergy relationships. Conformant with military strategies that frequently involve a combination of overt and covert operations to achieve an operational objective, we also propose an alternative model for sequential overt and covert deployment of subsets of interdiction resources, and conduct theoretical as well as empirical comparative analyses between models for purely overt (with or without synergy) and composite overt-covert strategies to provide insights into absolute and relative threshold criteria for recommended resource utilization. In contrast to existing static models, in a fourth application, we present a novel dynamic network interdiction model that improves realism by accounting for interactions between an interdictor deploying resources on arcs in a digraph and an evader traversing the network from a designated source to a known terminus, wherein the agents may modify strategies in selected subsequent periods according to respective decision and implementation cycles. We further enhance the realism of our model by considering a multi-component objective function, wherein the interdictor seeks to minimize the maximum value of a regret function that consists of the evader's net flow from the source to the terminus; the interdictor's procurement, deployment, and redeployment costs; and penalties incurred by the evader for misperceptions as to the interdicted state of the network. For the resulting minimax model, we use duality to develop a reformulation that facilitates a direct solution procedure using the commercial software BARON, and examine certain related stability and convergence issues. We demonstrate cases for convergence to a stable equilibrium of strategies for problem structures having a unique solution to minimize the maximum evader flow, as well as convergence to a region of bounded oscillation for structures yielding alternative interdictor strategies that minimize the maximum evader flow. We also provide insights into the computational performance of BARON for these two problem structures, yielding useful guidelines for other research involving similar non-convex optimization problems. For the fifth application, we examine the problem of apportioning railcars to car manufacturers and railroads participating in a pooling agreement for shipping automobiles, given a dynamically determined total fleet size. This study is motivated by the existence of such a consortium of automobile manufacturers and railroads, for which the collaborative fleet sizing and efforts to equitably allocate railcars amongst the participants are currently orchestrated by the \textit{TTX Company} in Chicago, Illinois. In our study, we first demonstrate potential inequities in the industry standard resulting either from failing to address disconnected transportation network components separately, or from utilizing the current manufacturer allocation technique that is based on average nodal empty transit time estimates. We next propose and illustrate four alternative schemes to apportion railcars to manufacturers, respectively based on total transit time that accounts for queuing; two marginal cost-induced methods; and a Shapley value approach. We also provide a game-theoretic insight into the existing procedure for apportioning railcars to railroads, and develop an alternative railroad allocation scheme based on capital plus operating costs. Extensive computational results are presented for the ten combinations of current and proposed allocation techniques for automobile manufacturers and railroads, using realistic instances derived from representative data of the current business environment. We conclude with recommendations for adopting an appropriate apportionment methodology for implementation by the industry.<br>Ph. D.

Thesis (Ph.D.)--Indiana University, Dept. of Anthropology, 2007.<br>Source: Dissertation Abstracts International, Volume: 68-09, Section: A, page: 3930. Adviser: Kevin D. Hunt. Title from dissertation home page (viewed May 8, 2008).

Thesis (DPhill (Social Work))—University of Stellenbosch, 2005.<br>South Africa has high levels of social need which are steadily growing. While the third sector is large and contributes substantially to social service provision, it together with government is seemingly incapable of providing adequate social services, particularly in the more poverty-stricken rural areas of the country. Among other, at the root of the third sector’s inability to adequately serve the needy, is a lack of funding caused by poor funding policies and uninformed financial resource allocation decision making. As such, this study set out to develop an automated financial resource allocation decision making model that would provide extensive organised data to better inform the allocation decision making process – the first component of the study. It was also purposed to provide a range of otherwise lacking empirical data on the third sector to determine service and staffing norms, patterns of funding and to assess financial management of this sector. In so doing the Community Chest of the Western Cape was selected to serve as the locus of the study – their existing manual allocation approach was analysed and a new more sophisticated automated model was developed. Data generated by the model pointed to a further research need, that of a better understanding of the funding and financial management practices of the third sector. This gave rise to the third component of the study, a survey of 232 beneficiary organisations of the Community Chest. An analysis of the data generated by the model and collected from the survey highlighted yet another need, the poor financial management acumen of the sector. In order to address this need and hence the efficacy of the model, a survey of 207 University of Cape Town management accounting students was conducted to determine the feasibility of using their financial management knowledge and skills to support financially and IT-illiterate organisations – the fourth component of the study. The study primarily adopted a quantitative research paradigm; the research design was exploratory-descriptive and used a primary data design with limited secondary data analysis. Data was captured in MS Access and analysed using Statistica and MS Excel. Results indicated that the country’s funding policies were wanting and that the allocation of state and state-controlled funding agency resources were not being allocated in concert with adopted policy. In almost all cases the poorer rural areas had and received fewer resources. Most organisations surveyed were not financially secured and their ability to fundraise was very limited. Their financial management ability was not good. Fortunately a substantial number of accounting students indicated a willingness to improve the financial management ability of such needy organisations. The study concludes by recommending further development of the model, utilisation of accounting students and calls for a major assessment of third sector needs, its funding and financial management. It also recommends the formulation of new funding policies.

Load control design is one of the major cornerstones of radio resource management in today's UMTS networks. A WCDMA cell's ability to utilize available spectrum efficiently, maintain system stability and deliver minimum quality of service (QoS) requirements to in-cell users builds on the algorithms employed to manage the load. Admission control (AC) and congestion control (CC) are the two foremost techniques used for regulating the load, and differing environments will place varying requirements on the AC and CC schemes to optimize the QoS for the entire radio network. This thesis studies a real-life situation where cells are put under strenuous conditions, investigates the degrading effects a high-speed train has on the cell's ability to maintain acceptable levels of QoS, and proposes methods for mitigating these effects. The scenario is studied with regard to voice traffic where the limiting radio resource is downlink power. CC schemes that take levels of fairness into account between on-board train users and outdoor users are proposed and evaluated through simulation. Methods to anticipatorily adapt radio resource management (RRM) in a cell to prepare for a train is proposed and evaluated through simulation. A method to detect a high-speed train in a cell, and the users on it, is outlined and motivated but not simulated. Simulation results are promising but not conclusive. The suggested CC schemes show a surprising tendency towards an increase in congestion avoidance performance. Proactive RRM shows a significant increase in QoS for on-board users. No negative effects to users in the macro environment is noticed, with regard to the studied metrics.

<p>Due to the unpredictability in job arrival times in clusters and widely varying resource requirements, dynamic scheduling of parallel computing resources is necessary to increase system throughput. Dynamically resizable applications provide the flexibility needed for dynamic scheduling. These applications can expand to take advantage of additional free processors, or to meet a Quality of Service (QoS) deadline, or can shrink to accommodate a high priority application, without getting suspended.</p> <p>This thesis is part of a larger effort to define a framework for dynamically resizable parallel applications. This framework includes a scheduler that supports resizing applications, an API to enable applications to interact with the scheduler, and libraries that make resizing viable. This thesis focuses on libraries for efficient resizing of parallel applications â efficient in terms of minimizing the cost of data redistribution, choosing and allocating the right set of additional processors, and focusing on the performance of the application after resizing. We explore the tradeoffs between these goals on both homogeneous and heterogeneous clusters. We focus on structured applications that have 2D data arrays distributed across a 2D processor grid.</p><p> Our library includes algorithms for processor selection and processor mapping. For homogeneous clusters, processor selection involves selecting the number of processors that needs to be added and processor mapping decides the placement of the new processors in the context of the given topology such that it minimizes the amount of data that is to be redistributed. For heterogeneous clusters, since the processing powers of the processors vary, there is also an additional problem of choosing the right set of processors that needs to be added. We also present results that demonstrate the effectiveness of our approach.</p><br>Master of Science

Thesis (Ph.D.)--Aerospace Engineering, Georgia Institute of Technology, 2008.<br>Committee Chair: Mavris, Dimitri; Committee Member: Bishop, Carlee; Committee Member: Costello, Mark; Committee Member: Kirby, Michelle; Committee Member: Schrage, Daniel

Effective and efficient use of public resources has a vital importance for Turkey, as for all countries. To serve this purpose, public financial management was reformed and performance budgeting system was begun to be implemented in Turkey. In order performance budgeting system to be properly put into practice, the system should have been well designed, regulations should have been adequately prepared and necessary information, guidance and support should be provided to the implementers. In this study, the implementation of performance budgeting system in Turkey was investigated from the perspective of public administrations under general budget and problems in the system were identified. Comments, experiences and suggestions of administrations were obtained via questionnaires and interviews, and analyzed. Additionally, regulatory legal documents and reports of administrations prepared within the performance budgeting concept were also investigated. In order to provide constitution of a more properly designed system and more easy and smooth implementation, to obtain a well adopted system by the implementers and to get results of better quality, proposals were put forward corresponding to the identified problems. Integrated analytic network process with a strategic resource allocation model proposal is presented to be used in update of performance programs in the aim of minimizing the deviations from targeted performance within budget constraints. The proposed model is implemented for the Strategy Development Unit of the Undersecretariat of Treasury.

<p>Bakgrund: Det finns en rad olika faktorer som påverkar produktutvecklingsprocessen vid ett företag. Isaberg Rapid AB utvecklar, tillverkar och marknadsför en rad produkter inom tre olika produktområden; kontor, verktyg och OEM. Denna studie fokuserar på produktutvecklingsprocesserna inom divisionen för kontorsprodukterna vilken kanske är den mest konkurrentutsatta på företaget. Produkterna som tillhandahålls av divisionen är under hårt tryck från konkurrenter på en global basis och snabba och effektiva produktsläpp är av yttersta vikt för att hävda sig på marknaden. De olika aktiviteterna omkring produktutveckling i kombination med de snabba förändringarna av företagets marknadssituation med nya kundgrupper och ökande konkurrens, har lett fram till vissa specifika ofrånkomliga faktorer som har en stor inverkan på produktutvecklingens effektivitet. Detta resonemang leder sedermera fram till uppsatsens syfte.</p><p>Syfte: Syftet med uppsatsen är primärt att identifiera, och påvisa samband mellan, faktorer som påverkar utvecklingen av nya produkter vid Isaberg Rapid AB och sekundärt att påvisa brister i hanteringen av dessa.</p><p>Metod: Syftet har uppfyllts genom att använda en kvalitativ ansats där olika befattningshavare rörande produktutvecklingen på Isaberg Rapid AB har intervjuats. Även observationer har gjorts med avsikten att erhålla en djupare insyn i företagets arbetssätt och ingående funktioner. Referensramens teori och modeller användas för att belysa iakttagelserna i analysen på ett systematiskt sätt och för att förstå syftet. Intervjuerna har utförts enligt en semikonstruerad metod. Utfallet från intervjuerna har sedan analyserats, där fokus i första hand är övergripande, följt av de mer ämnesspecifika frågorna.</p><p>Slutsatser: Vår studie har visat att genom att förbättra sammansättningen mellan långa och korta projekt med hög resp. låg risk kan projektportföljens strategiska och värdemässiga aspekter förbättras. Produktutvecklingen bör fokuseras på att utnyttja projektportföljen som ett kraftfullt instrument, för att utvecklingen inte ska tendera att styras över till orätta projekt på bekostnad av andra mera rätta projekt. Isaberg Rapid måsta således vara ledande inom produktutveckling, och överglänsa konkurrenterna genom att satsa på ny teknologi och våga ta risker, detta uppenbaras av framgångarna med Duax. Effektivare utveckling uppnås endast genom korrekta resursallokeringar och en snabb utvecklingstid, vilket dock fordrar en väl fungerande produktutvecklingsprocess. Då kan syftet infrias och målet uppnås.</p><br><p>Background: There are a number of different factors, affecting the product development process at a company. Isaberg Rapid AB develops, manufacture and sell products within three different business areas; office, tools and OEM. This essay focuses on the product development process at the office division of the company; perhaps the most competitively pressured division of the company. The products handled by the division are under hard pressure from competitors on a global basis and fast and effective product launches are highly important to maintain the position on the market. The activities associated with product development combined with a changing market situation have led to certain inevitable factors that deeply affect the efficiency of the product development process. These arguments eventually lead up to the purpose of this thesis.</p><p>Purpose: The purpose of the thesis is primarily to identify, and point out connections between, factors affecting the development of new products at Isaberg Rapid AB, and secondary to point out failures in the handling of those.</p><p>Method: using a qualitative method where different employees concerned with product development activities at the company have been interviewed has fulfilled the purpose. Observations to obtain a deeper company insight have also been performed. Theories and models from the frame of reference have been used to analyze the empirical findings systematically in order to understand the purpose. The interviews have been held in a semi constructed way. The results form the interviews have been analyzed with both a general focus and later on specified to the identified subjects.</p><p>Conclusions: Our study has shown that the balance of the project portfolio in terms of long and short projects with high and low risk could be improved in terms of value and strategic aspects. Product development should be focused on utilizing the project portfolio as a powerful instrument, in order to avoid that the development tendons to choose a wrong project on behalf of others more right ones. Isaberg Rapid must in this manner leading the product development, and be ahead of its competitors by investing in new technology and be willing of taking risks, that the success with Duax has proven right. Effective product development is achieved by allocating the recourses right and provide for a fast time to market cycle, which however insist on a well-functioned product development. Then can the purpose be fulfilled and the objectives achieved totally.</p>

Face un environnement complexe et hyper-compétitif, les firmes sont amenées à reconsidérer leur modèle de création de valeur. Leur réaction s’insère dans le cadre d’une réinvention voire innovation de leur Business Model (BM). Ceci passe indéniablement par une démarche d’expérimentation stratégique. Définie comme un processus par lequel les firmes explorent de nouvelles sources de revenus et testent de nouveaux concepts d’affaires, l’expérimentation stratégique s’associe à un outil de réinvention du BM qui intervient non seulement dans la création de nouveaux BM mais également dans la transformation de BM existants. Nous posons ainsi la question de savoir : Comment concevoir l’expérimentation stratégique des BM des entreprises ? Dans cette perspective, notre recherche vise à dresser un cadre conceptuel et méthodologique de l’expérimentation stratégique. Il s’agit de proposer aux entreprises une aide à la conception d’une méthodologie d’expérimentation de BM. Pour répondre à cette problématique, nous proposons de définir l’expérimentation stratégique comme une théorie combinée du changement en partant du modèle de Van de Ven et Poole (1995) sur les théories de changement et de développement organisationnel. Ceci permet de traduire les processus centraux de l’expérimentation stratégique et d’en saisir les dimensions clés. Dans le cadre d’une approche qualitative avec étude de cas, nous interrogeons trois profils d’acteurs sur leurs registres de conception et de pratique de l’expérimentation. Ensuite, nous élaborons via une analyse inter-profils un modèle générique d’expérimentation stratégique de BM qui s’articule autour de trois temps de l’expérimentation stratégique ; un temps de virtualisation, un temps d’actualisation et un temps d’itérations de processus de rationalisation et d’apprentissage<br>In a hypercompetitive environment, firms are obliged to reconsider their revenue formula and to innovate consequently the way they create value and make profit. This lies at the heart of every company’s ability to experiment new Business Models (BM) and becomes a key step in the strategic thinking. Defined as a process by which firms explore new ways of doing business, strategic experimentation takes shape of series of trial and error changes pursued along various dimensions of strategy in an effort to identify and establish a viable basis for competing. Our research examines strategic experimentation as an effective tool for BM reinvention. It answers therefore to the main question of: How to conceive BM experimentation? In this way, we define strategic experimentation as a combined theory of change according to the model developed by Van de Ven and Poole (1995) to explain processes of organizational development and change. We aim at dressing a conceptual and methodological framework for strategic experimentation that would helps managers and academics to conceive and master the process of BM experimentation. Using a qualitative research methodology rooted in a case study approach, we achieved semi-structured interviews with three categories of actors implied in the process of BM experimentation. Our results demonstrate that BM experimentation is organized through four major processes which are exploration, formulation, resources allocation and identification which are articulated by a time of virtualization, a time of actualization, and a time of iterations based on learning and rationalization

Le choix social repose sur l’étude de la prise de décision collective, où un ensemble d’individus doit convenir d’une solution commune en fonction des préférences de ses membres. Le problème revient à déterminer comment agréger les préférences de différents agents en une décision acceptable pour le groupe. Typiquement, les agents interagissent dans des processus de décision collective, notamment en collaborant ou en échangeant des informations. Il est communément supposé que tout agent est capable d’interagir avec n’importe quel autre. Or, cette hypothèse paraît irréaliste pour de nombreuses situations. On propose de relâcher cette hypothèse en considérant que la possibilité d’interaction est déterminée par un réseau social, représenté par un graphe sur les agents. Dans un tel contexte, on étudie deux problèmes de choix social : le vote stratégique et l’allocation de ressources. L’analyse se concentre sur deux types d’interaction : la collaboration entre les agents, et la collecte d’information. On s’intéresse à l’impact du réseau social, modélisant une possibilité de collaboration entre les agents ou une relation de visibilité, sur la résolution et les solutions de problèmes de vote et d’allocation de ressources. Nos travaux s’inscrivent dans le cadre du choix social computationnel, en utilisant pour ces questions des outils provenant de la théorie des jeux algorithmique et de la théorie de la complexité<br>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

Resource management for a data center with multiple job classes is investigated in this thesis. We focus on strategies for allocating resources to an application mix such that the service level agreements (SLAs) of individual applications are met. A performance model with two interactive job classes is used to determine the smallest number of processor nodes required to meet the SLAs of both classes. For each class, the SLA is specified by the relationship: Prob(response time≤x)≥y. Two allocation strategies are considered: shared allocation (SA) and dedicated allocation (DA). For the case of FCFS scheduling, analytic results for response time distribution are used to develop a heuristic algorithm that determines the allocation strategy (SA or DA) that requires fewer processor nodes. The effectiveness of this algorithm is evaluated over a range of operating conditions. The performance of SA with non-FCFS scheduling is also investigated. Among the scheduling disciplines considered, a new discipline called probability dependent priority (PDP) is found to have the best performance in terms of requiring the smallest number of nodes. Furthermore, we extend our heuristic algorithm for FCFS to three job classes. The effectiveness of this extended algorithm is evaluated. As to priority scheduling, the performance advantage of PDP is also confirmed for the case of three job classes.

She, Yingni.<br>Thesis (M.Phil.)--Chinese University of Hong Kong, 2009.<br>Includes bibliographical references (leaves 74-78).<br>Abstracts in English and Chinese.<br>Chapter 1 --- Introduction --- p.1<br>Chapter 1.1 --- Scope --- p.2<br>Chapter 1.2 --- Motivation --- p.5<br>Chapter 1.3 --- Structure of the Thesis --- p.6<br>Chapter 2 --- Literature Review --- p.7<br>Chapter 2.1 --- Intelligent Agents and Multiagent Systems --- p.8<br>Chapter 2.1.1 --- Intelligent Agents --- p.8<br>Chapter 2.1.2 --- Multiagent Systems --- p.10<br>Chapter 2.2 --- Minority Game --- p.13<br>Chapter 2.2.1 --- Minority Game --- p.13<br>Chapter 2.2.2 --- Characteristics of Minority Game --- p.14<br>Chapter 2.2.3 --- Strategies for Agents in Minority Game --- p.18<br>Chapter 2.3 --- Resource Allocation --- p.22<br>Chapter 2.3.1 --- Strategies for Agents in Multiagent Resource Allocation --- p.23<br>Chapter 3 --- Individual Agent´ةs Wealth in Minority Game --- p.26<br>Chapter 3.1 --- The Model --- p.26<br>Chapter 3.2 --- Motivation --- p.27<br>Chapter 3.3 --- Inefficiency Information --- p.28<br>Chapter 3.4 --- An Intelligent Strategy --- p.31<br>Chapter 3.5 --- Experiment Analysis --- p.32<br>Chapter 3.6 --- Discussions and Analysis --- p.35<br>Chapter 3.6.1 --- Equivalence to the Experience method --- p.36<br>Chapter 3.6.2 --- Impact of M' and S' --- p.38<br>Chapter 3.6.3 --- Impact of M and S --- p.41<br>Chapter 3.6.4 --- Impact of Larger Number of Privileged Agents --- p.48<br>Chapter 3.6.5 --- Comparisons with Related Work --- p.48<br>Chapter 4 --- An Adaptive Strategy for Resource Allocation --- p.53<br>Chapter 4.1 --- Problem Specification --- p.53<br>Chapter 4.2 --- An Adaptive Strategy --- p.55<br>Chapter 4.3 --- Remarks of the Adaptive Strategy --- p.57<br>Chapter 4.4 --- Experiment Analysis --- p.58<br>Chapter 4.4.1 --- Simulations --- p.58<br>Chapter 4.4.2 --- Comparisons with Related Work --- p.62<br>Chapter 5 --- Conclusions and Future Work --- p.69<br>Chapter 5.1 --- Conclusions --- p.69<br>Chapter 5.2 --- Future Work --- p.71<br>A List of Publications --- p.73<br>Bibliography --- p.74

It is generally agreed that communication is a critical technological factor in designing networked unmanned systems (NUS) that consist of a large number of heterogeneous assets/nodes that may be configured in ad-hoc fashion and that incorporate intricate architectures. In order to successfully carry out the NUS missions, communication among assets need to be accomplished efficiently. In contrast with conventional networks, NUSs have specific features that may render communication more complex. The main distinct characteristics of NUS are as follows: (a) heterogeneity of assets in terms of resources, (b) multiple topologies that can be fully-connected, (c) real-time requirements imposed by delivery timeliness of messages under evolving and uncertain environments, (d) unknown and random time-delays that may degrade the closed-loop dynamics performance, (e) bandwidth constraints reflecting differences in assets behavior and dynamics, and (f) protocol limitations for complying with the wireless features of these networks. The NUS system consists of clusters each having three nodes, namely, a sensor, a decision-maker, and an actuator. Inspired by networked control systems (NCS), we introduced a generic framework for NUSs. Using the fluid flow model (FFM), the overall dynamical model of our network cluster is derived as a time-delay dependent system. The following three main issues are investigated in this thesis, bandwidth allocation, an integrated bandwidth allocation and flow rate control, and congestion control. To demonstrate the difficulty of addressing the bandwidth allocation control problem, a standard PID is implemented for our network cluster. It is shown that in presence of feedback loops and time-delays in the network, this controller induces flow oscillations and consequently, in the worst-case scenario, network instability. To address this problem, nonlinear control strategies are proposed instead. These strategies are evaluated subject to presence of unknown delays and measurable/estimated input traffic. For different network configurations, the error dynamics of the entire controlled cluster is derived and sufficient stability conditions are obtained. In addition, our proposed bandwidth allocation control strategy is evaluated when the NUS assets are assumed to be mobile. The bandwidth allocation problem is often studied in an integrated fashion with the flow rate control and the connection admission control (CAC). In fact, due to importance of interaction of various components, design of the entire control system is often more promising than optimization of individual components. In this thesis, several robust integrated bandwidth allocation and flow rate control strategies are proposed. The third issue that is investigated in this thesis is the congestion control for differentiated-services (DiffServ) networks. In our proposed congestion control strategies, the buffer queue length is used as a feedback information to control locally the queue length of each buffer by acting on the bandwidth and simultaneously a feedback signaling notifies the ordinary sources regarding the allowed maximum rate. Using sliding mode generalized variable structure control techniques (SM-GVSC), two congestion control approaches are proposed, namely, the non degenerate and degenerate GVS control approaches. By adopting decentralized end-to-end, semi-decentralized end-to-end, and distributed hop-by-hop control approaches, our proposed congestion control strategies are investigated for a DiffServ loopless mesh network (Internet) and a DiffServ fully-connected NUS. Contrary to the semi-decentralized end-to-end congestion control strategy, in the distributed hop-by-hop congestion control strategy, each output port controller communicates the maximum allowed flow rate only to its immediate upstream node(s) and/or source(s). This approach reduces the required amount of information in the flow control when Compared to other approaches in which the allowed flow rate is sent to all the upstream sources communicating through an output port.

The new approach of cloud robotics takes advantage of cloud computing as a vast resource pool for massively parallel computation and sharing of data. Besides, the cloud robotic system removes overheads for maintenance and updates, and reduces dependence on user middleware. This is of particular interest for service robots, because on-board computation entails additional power requirements which may reduce operating duration and constrain robot mobility as well as costs. In order to utilize the cloud technology in service robots, it is crucial to allow different types of robots to share information and to develop new skills on the cloud.<br>In general, it is cast as a dynamic resource allocation problem. Given a set of resources and a sequence of agents, the goal is to distribute resources to agents in an optimal manner. The resource allocation problem is an NP-hard problem in general. This thesis strives to minimize the resource usage and task completion time by scheduling a number of requests from robots. However, actual realization of fully distributed cloud robotic systems is rarely found in the community. Moreover, unconstrained resources in the cloud are not commonly implemented. Therefore, the optimization of autonomously implemented resource allocation is the primary focus of the thesis.<br>While a respectable amount of work is done on both resource and task allocation, there is still the need for research towards the integration of problems in a typical cloud robotic system. For the outlined difficulties, this thesis addresses novel research on the following aspects: At first, the underlying architecture of Multi Sensor Data Retrieval (MSDR) is implemented on the twisted-based socket for asynchronous data transmission, which is also investigated as effective decentralized methods for multi-robot coordination, task assignment and service contract establishing. Second, the market-based scheduling mechanism is proposed for the dynamic resource allocation problem in cloud robotics. A set of criteria as empirical Quality of Service (QoS) is optimized, especially Time to Response (ToR) is minimized to fulfill Firm Real-Time (FRT) requirement of robotic tasks. Third, a Link Quality Matrix (LQM) auction-based negotiation strategy is proposed to relieve the competition among multi-robot systems in Mobile Ad-hoc Networks (MANETs). Besides, an incremental auction-based strategy is proposed considering hops, time delay as well as link quality. Both fair allocation when unmanned interference and biased allocation when users have preferences are optimized among multi-robot systems in MANETs. By tackling all these issues, this thesis contributes to general implementation of cloud robotic system into daily.<br>Future research will focus on task-oriented problems, such as smart home surveillance, guiding and etc., which could be better solved benefiting from cloud robotics. Solutions will proposed in a bidirectional way considering both data uploading and downloading.<br>雲機器人是利用雲計算作為龐大的資源池進行大規模并行計算和資源共用。此外，雲機器人系統避免了用於維護和更新各個機器人客戶端的開銷，並降低了機器人客戶端對中間件的依賴。這對於服務機器人尤其有益，因為大量計算所需要的能量會減少機器人運行的持續時間，並且約束機器人移動性能以及增加機器人的成本。爲了更好的利用雲技術提高機器人的服務性能，最重要的是允許不同類型的機器人共用資源，尤其是多傳感器的信息，並在雲上開發新的功能和新的應用。<br>此類問題一般被規劃為動態資源配置問題，即給定一個資源集合和一個多客戶端的序列，最優化地進行資源的分配。資源配置問題是一個非確定性多項式複雜 (NP-hard) 問題 。本文通過優化調度多個資源請求，力求最大限度地減少資源的使用和任務完成的時間。目前很少有真正實現了完全分布式的雲機器人系統。此外，在實際的雲系統中並不存在無限的不受約束的資源。因此，自主地優化雲機器人系統的資源配置是雲機器人系統的關鍵問題，有著重要的現實意義。<br>雖然在資源配置和任務分配領域已經有大量的研究工作，當這兩者在典型的雲機器人系統中結合時，仍然有大量新的問題需要研究。本文著重於以下幾個方面：首先，建立多傳感器資料的檢索架構，即基於twisted的socket 框架建立任務分配和服務合同的構建方法，用於實現多傳感器信息的異步傳輸，同時將其用於研究有效的分布式多機器人協作。其次，提出基於市場范式的調度機制，用於解決雲計算機器人系統的動態資源配置問題；並針對一系列服務品質指標進行優化和驗證，特別是實現回應時間的最小化，以滿足機器人任務即時性的要求。第三，提出基於鏈路信號強度矩陣的協商策略以減輕在移動自組網路中多個機器人的通信競爭；此外，考慮到多跳、時延和鏈路品質等問題，本文提出了增量式的拍賣算法策略；當移動自組網中存在多機器人系統時，所涉算法對無人干擾情況下的公平分配和當有使用者有偏好情況下的偏好分配分別進行了優化。通過解決以上問題，本文的貢獻有助於通用的雲機器人系統融入到人類日常生活和工作中。<br>未來的研究將側重于面向機器人任務分配的問題，例如監控，多機器人嚮導等，及其他受益于雲機器人平臺的各類應用解決方案。<br>Wang, Lujia.<br>Thesis Ph.D. Chinese University of Hong Kong 2014.<br>Includes bibliographical references (leaves 115-127).<br>Abstracts also in Chinese.<br>Title from PDF title page (viewed on 07, October, 2016).<br>Detailed summary in vernacular field only.<br>Detailed summary in vernacular field only.<br>Detailed summary in vernacular field only.<br>Detailed summary in vernacular field only.

博士<br>國立成功大學<br>電機工程學系碩博士班<br>91<br>Future IMT-2000 (International Mobile Telecommunications after the year 2000) are expected to be integrated by terrestrial and satellite components to provide a seamless, wide rang of coverage areas, system capacity, and available service types for personal communications. In the space segment, low-earth orbit (LEO) satellite based systems are preferred with the consideration of some technical issues such as transmission delay, path loss, antenna aize, etc.. However, because of the short period for which the satellites are visible, users of LEO satellite systems face frequent handoff requirements between spot-beams (cells). In the terrestrial part, cellular communication infrastructures envision to adopt hierarchical, multisized cells for covering non-homogeneous populated areas. Microcells have significantly higher capacity than large cells and are more cost-effective in reducing power consumption in densely populated districts. Meanwhile, large cell systems (macrocells) avoid the need for frequent cell boundary crossings (handovers) to serve high mobility mobile users. In this thesis, based on the different features of the terrestrial and LEO satellite-based systems, we study some channel and power allocation strategies and show that these schemes can provide larger capacity and better performance for the cellular communication systems.

博士<br>國立成功大學<br>電機工程學系碩博士班<br>91<br>Nowadays, in the evolution toward the next-generation mobile system, a wide range of services (such as high quality voice, data, electronic mail, facsimile, video and interactive applications) has imposed itself as an essential demand of the universal communications. To efficiently utilize the radio resource of mobile systems and provide services of high quality for all users, radio resource management has become a noticeably important issue in a service-integrated mobile cellular system. Therefore, we are motivated to investigate and develop resource-allocation strategies for integrated services in mobile cellular systems. The most principal concept of the proposed strategies is to schedule the data transmissions in accordance with the load of voice traffic and to ensure the predefined quality of service (QoS) requirements of all connections. In this dissertation, we first propose a resource-allocation strategy to integrate packet-switched data traffic into current TDMA-type circuit-switched digital voice system. This integrated system transmits data packets during the silent periods of a conversation with voice activity detection and adapts itself to GSM/GPRS system which uses the idle channels to provide data service. We show that the proposed strategy can increase the bandwidth utilization efficiency and improve throughput/delay performance of the data transmission, while minimize he impacts on current GSM/GPRS system. Then, we study the effect of voice activity on the system performance in a voice-oriented CDMA sys-tem. We present a general analytical methodology to evaluate the capacity gain due to voice activity and the time duration of idle period of multiaccess link. It is demonstrated that a lot of unused capacity and a long enough idle period of multiaccess link can be employed to send the packet-switched data traffic. Last, we investigate the resource-allocation strategy for an integrated voice/data cellular CDMA system. The delay-sensitive voice traffic has a higher priority to use the channel resource, whereas the error-sensitive data traffic has a higher priority to use the power resource. Three power resource allocation schemes are compared: equal power scheme, equal service-reliability scheme, and robust data scheme. By means of the power resource allocation and the admission control, the sys-tem can offer different service reliability (and QoS) to voice and data services. The concept of guard channel is used as interference margin to improve the service reliability. This integrated CDMA sys-tem is analyzed for two cases : 1) system with .xed length data traffic and 2) system with variable length data traffic. Different from the former one, the system with variable length data traffic employs a two-level admission control policy, which consists of a call-admission control and a packet-level admission control, and adopts a dynamic guard-channel scheme to tune the system performance.

Next generation wireless networks are expected to provide high data rate and satisfy the Quality-of-Service (QoS) constraints of the users. A significant component of achieving these goals is to increase the effi ciency of wireless networks by either optimizing current architectures or exploring new technologies which achieve that. The latter includes revisiting technologies which were previously proposed, but due to a multitude of reasons were ignored at that time. One such technology is relaying which was initially proposed in the latter half of the 1960s and then was revived in the early 2000s. In this dissertation, we study relaying in conjunction with resource allocation to increase the effi ciency of wireless networks. In this regard, we differentiate between conventional relaying and relaying with buffers. Conventional relaying is traditional relaying where the relay forwards the signal it received immediately. On the other hand, in relaying with buffers or buffer-aided relaying as it is called, the relay can store received data in its buffer and forward it later on. This gives the benefit of taking advantage of good channel conditions as the relay can only transmit when the channel conditions are good. The dissertation starts with conventional relaying and considers the problem of minimizing the total consumed power while maintaining system QoS. After upper bounding the system performance, more practical algorithms which require reduced feedback overhead are explored. Buffer-aided relaying is then considered and the joint user-and-hop scheduler is introduced which exploits multi-user diversity (MUD) and 5 multi-hop diversity (MHD) gains together in dual-hop broadcast channels. Next joint user-and-hop scheduling is extended to the shared relay channel where two source-destination pairs share a single relay. The benefits of buffer-aided relaying in the bidirectional relay channel utilizing network coding are then explored. Finally, a new transmission protocol for overlay cognitive radios is derived. This protocol utilizes relays with buffers, requires only causal knowledge of the primary's message at the secondary and incentivizes the primary to cooperate with the secondary and share its codebook.

碩士<br>國立臺灣大學<br>資訊管理學研究所<br>100<br>In the past, individuals and enterprises are usually the main subjects in the area of information security. Now the issue about information warfare between nation-sates is getting much attention. When discussing the resource allocation based on the subject of a nation-state, except for the allocation of defense resources, the resources allocated on attack should also be concerned. Historically, preventive strike and the corresponding retaliation from another nation-state are common in the war between two nation-states. In addition, there would be various information experts launching an attack together for a nation-state, which is called collaborative attacks that different from the situation of only one attacker in an ordinary cyber attack. Therefore, we consider two players that could attack and defend simultaneously and adopt the concept of collaborative attacks in our research model. How to efficiently evaluate the network survivability is an important issue and worthy of discussion. In this thesis, the Average Degree of Disconnectivity (Average DOD) metric is adopted to measure the network survivability. The Average DOD combines the concept of probability with DOD metric to evaluate the damage degree of the network. The larger the Average DOD value, the higher the damage degree of the network. In our scenario, there are two players who have the dual-roles as an attacker and a defender; furthermore, both of them do not know the vulnerability information about their networks. However, the counterpart knows some. Therefore, after being attacked, they would update their vulnerabilities information and patch the vulnerabilities. We develop a multi-round network attack-defense scenario, and establish a mathematical model to optimize resource allocation and then predict their own network survivability by the Average DOD. In each round, the players could allocate their attack resources on the nodes of their own network and on another player’s network after updating related information about another player’s. Furthermore, they could reallocate existing defense resources and repair compromised nodes. To solve the problem, the “gradient method” and “game theory” would be adopted to find the optimal resource allocation strategies for both players.

<p>The mobile wireless environment has been a challenge to reliable communications because of the time-varying nature of the channel. Detrimental effects such as path loss, shadowing, and multipath fading can greatly attenuate the transmitted signal. Therefore, adaptive channel estimation and data detecting algorithms must be designed for such channels. Moreover, in a multi-user system, dynamic resource allocation is an important means to transmit information efficiently through the varying channel.</p> <p>In this thesis we first propose two adaptive feedback maximum-likelihood detection techniques, a decision-feedback decoder and an output-feedback decoder, for coded signals transmitted over channels with correlated fading. Both analysis and simulation results demonstrate that they have far better performance than the conventional decoder. We also propose a simple improvement to conventional decoders by using a weighted metric. The BER performance of all these decoders is analyzed through a sliding window decoding method.</p> <p>Next we derive the ergodic (Shannon) capacity region and optimal dynamic resource allocation for an M-user fading broadcast channel under code-division with and without successive decoding, time-division, and frequency-division. For this channel we also derive the outage and zero-outage capacity regions and the corresponding optimal resource allocation strategies under different spectrum-sharing techniques. We obtain the outage capacity region implicitly by deriving the minimum common outage probability or the outage probability region for a given rate vector. The corresponding optimal power allocation scheme is a multi-user generalization of the single-user threshold-decision rule.</p> <p>Finally, we obtain the outage capacity region and optimal power allocation for fading multiple access channels. Successive decoding is proved to be optimal and iterative algorithms are proposed to obtain the optimal decoding order and power allocation in each fading state under the average power and outage probability constraints of each user. We also obtain the average power regions that can support a rate vector with the given average outage probability of each user satisfied.</p>

博士<br>國立中央大學<br>電機工程研究所<br>100<br>The leading technologies specified in IEEE 802.16 standards have been evolved the most promising solutions in broadband wireless access networks. Having defined four types of service, the IEEE 802.16 standard still left the implementation of resource allocation supporting the four various qualities of service classes and admission control confining the number of flows entering the network as an open issue. Up to this point, however, this issue which has been touched and explored from time to time demonstrates that there is still room for much promotion. Thus, this study aims to explore dynamic bandwidth allocation algorithms in IEEE 802.16 time division duplex broadband wireless access networks under symmetric and/or asymmetric uplink and downlink traffic input, particularly in terms of accumulated throughput, fairness, and packet drop ratio in both infinite and finite buffer cases compared with others by simulations. The major results reveal that the proposed algorithm not only can provide much better fairness and maintain satisfactory quality of service support and high cumulative bandwidth but also in the case of the finite buffer depth is less buffer-consuming than the others, meaning that the hardware cost can be reduced by employing the proposed algorithm. In addition, a multiple cross-layer handover scheme using optimized MIH services in IEEE 802.16e networks is also involved. The thorough analyses of handover scenario show that the proposed scheme not only can reduce handover disruption time but also has no packet loss than the others. The two proposed solutions may help to compensate IEEE 802.16 standards for missing parts and to achieve seamless handovers in IEEE 802.16e networks, respectively.

碩士<br>國立臺灣大學<br>資訊管理學研究所<br>102<br>With the rapid growing of the Internet, information system has become an irreplaceable part of the businesses daily operation. However, although the Internet brings lots of advantages but also brings more threats to the businesses. It would create devastating financial and reputation damage to the business once the information system which is connected to the Internet is destroyed under cyber attack and caused the normal course of operations disrupted. Hence, it is important to efficiently allocate defense resource for the defender. In the defense strategy of the defender, besides traditional method to protect system, deception is another effective mechanism with the incomplete information between the defender and the attacker. Through deception, the false targets can be used to reduce the probability that the genuine targets are under attack and encounter less-attack effort to achieve the goal of protecting genuine targets from destruction. Therefore, it is an important issue to decide resources allocation strategies with the defense strategy includes false targets and additional deception under limited resources. For this reason, we construct a model under the malicious attack with attack preference and the objective of the defender is to maximize the residual working capability while the objective of the attacker is to minimize that value. In our attack-defense scenario, the attacker can allocate part of budgets into exploring the system to obtain the evaluation of whether the target is valuable. When the value of evaluation is higher, it is more likely to be a genuine target. Therefore, the attacker can choose the targets to attack based on the evaluation and allocate proper resources to attack in the attack phase. In the view of the defender, besides deploys false targets, additional deception mechanisms can be used to interfere the evaluation of the attacker. Finally, the contest success function is adopted to evaluate the result and get the optimal solution in this problem.