Dissertations / Theses on the topic 'Resource allocation model'

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1986.
MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING.
Bibliography: leaves 351-354.
by Peng-Teng Peter Ng.
Ph.D.

Australian universities are multi-million dollar operations employing tens of thousands of people. They attract revenue from a variety of government and non-government sources, and yet, as non-profit organisations they are judged by governments, peers and their communities on their performance in teaching and research rather than on a financial bottom line. In order to achieve these results, university managers must make decisions on how to allocate available funding throughout the university. Faced with competing demands on scarce funds, how do university managers make these choices? One option is to use a resource allocation model to 'crunch the numbers'. Resource allocation models can incorporate a number of elements - student and staff numbers, weightings and performance data, for example - to allocate available funds. These allocation models are used in different ways in different universities, but serve the same basic purpose of assisting decision-making on how much to allocate to different sections of the organisation. Such models operate within a process and context that includes the strategic aims of the University, the organisation structure, its committees and culture. This thesis contains case studies of resource allocation models and processes used in three Australian universities. It examines the methods used for resource allocation at the first and second levels within each university; that is, from the Vice-Chancellor to Dean (or equivalent), and from Dean to Head of School (or equivalent). Observations and conclusions are drawn on the models used, the processes surrounding the models, and the continuity between the two layers of allocations. The research finds all the case-study universities operate models at multiple levels in their organisations, and that there is a concerning lack of consistency and flow-through at these different levels. The messages that the university leadership intends to send through the allocations may be lost to managers one-process removed from them. The research also concludes that transparency is the most important element of the resource allocation process. University staff dealing with allocation processes will accept the results, even if they are not ideal, if they can understand how and why decisions were made. As a professional doctorate thesis, the aim is to provide a practical aid to people with responsibility for resource allocation in universities.

The paper is an enquiry into dynamic social contract theory. The social contract defines the rules of resource use. An intergenerational social contract in an economy with a single exhaustible resource is examined within a framework of an overlapping generations model. It is assumed that new generations do not accept the old social contract, and access to resources will be renegotiated between any incumbent generation and their successors. It turns out that later generations will be in an unfortunate position regardless of their bargaining power.

This thesis explores the potential for providing processes with control over their resource allocation in a general-purpose distributed system. Rather than present processes with blind explicit control or leave the decision to the operating system, a compromise, called process-centric resource allocation is proposed whereby processes have informed control of their resource allocation, while the operating system ensures fair consumption. The motivations for this approach to resource allocation and its background are reviewed culminating in the description of a set of desired attributes for such a system. A three layered architecture called ERA is then proposed and presented in detail. The lowest layer, provides a unified framework for processes to choose resources, describe their priority and describes the range of available resources. A resource information mechanism, used to support choices of distributed resources then utilises this framework. Finally, experimental demonstrations of process-centric resource allocation are used to illustrate the third layer. This design and its algorithms together provide a resource allocation system wherein distributed resources are shared fairly amongst competing processes which can choose their resources. The system allows processes to mimic traditional resource allocations and perform novel and beneficial resource optimisations. Experimental results are presented indicating that this can be achieved with low overhead and in a scalable fashion.

An ecologically based model of forest succession is presented. In the model, trees compete for a share of limited growth resources available from their environment. Competition is reflected by each tree's effect on the resource pool and is not explicitly modeled. Model parameters were fit to field data from subalpine forests of the Rocky Mountains. A technique for estimating model parameters from understory-tolerance rankings and silvical characteristics of each species is also presented. The model's output was consistent with our current understanding of forest dynamics. Emergent properties of the model also mimicked natural processes such as self-thinning, release, and maximum stand basal area as a function of species present and site quality.

In this work we examine a state constrained resource allocation model a with finite time horizon. Therefore, we use the necessary conditions of the Pontrjagin's Maximum Principle to find candidates for the solution and verify them later on using the sufficient conditions given by the duality concept of Klötzler. Moreover, we proof that the solution of the corresponding infinite horizon model does not fulfill the overtaking criterion of Weizsäcker.

The allocations of health care resources in Bangladesh are not based on the needs of the population. Equality in health care expenditure can be achieved by the use of needs-based resource allocation formulae. Applying such methods in Bangladesh can provide an essential guideline to achieve equality in resource allocation. This thesis examines the prospect of developing a needs-based allocation of health care resources. It attempts to address the counterfactual question of what would have been the allocation to each district had the needs of the population been accounted for. Two alternative approaches are considered. The first uses a simple capitation formula in which weights for the adjustment of the current allocation are generated directly based on the relative values of proxies for needs. The second approach predicts adjustment weights from the estimation of a standard econometric model of needs, controlling for a range of determinants including individual, household and district characteristics. Important predictors of current allocation were found to be the number of hospital beds and health workers rather than need factors. Important predictors of needs include demographic and socio-economic characteristics. The findings suggest that a needs-based allocation can be developed for Bangladesh. This research provides an alternative approach to generating weights showing systematic relationships between the need adjustment factors. The robustness of the methods used will be sensitive to the quality of the data and the assumptions of the models. As these approaches are based on sound economic analysis and are open to independent assessment, they will help to inform policy debate and can reduce the influence of politically motivated allocations. A gradual process of implementation and regular review of the methods used would be a way forward. Future areas of research may include: re-analysing data at smaller area level and use of different components of allocations.

Construction projects are complicated and fraught with so many risks that many projects are unable to meet pre-defined project objectives. Managers of construction projects require decision support tools that can be used to identify, analyze and implement measures that can mitigate the effects of project risks. Several risk analysis techniques have been developed over the years to enable construction project managers to make useful decisions that can improve the chances of project success. These risk analysis techniques however fail to simultaneously address risks relating to cost, schedule and quality. Also, construction projects may have scarce resources and construction managers still bear the responsibility of ensuring that project goals are met. Certain projects require trade-offs between technical and managerial risks and managers need tools that can help them do this. This thesis evaluates the usefulness of the Advanced Programmatic Risk Analysis and Management Model (APRAM) as a decision support tool for managing construction projects. The development of a visitor center in Midland, Texas was used as a case study for this research. The case study involved the implementation of APRAM during the concept phase of project development to determine the best construction system that can minimize the expected cost of failure. A risk analysis performed using a more standard approach yielded an expected cost of failure that is almost eight times the expected cost of failure yielded by APRAM. This study concludes that APRAM is a risk analysis technique that can minimize the expected costs of failure by integrating project risks of time, budget and quality through the allocation of resources. APRAM can also be useful for making construction management decisions. All identified component or material configurations for each alternative system however, should be analyzed instead of analyzing only the lowest cost alternative for each system as proposed by the original APRAM model. In addition, it is not possible to use decision trees to determine the optimal allocation of management reserves that would mitigate managerial problems during construction projects. Furthermore, APRAM does not address the issue of safety during construction and assumes all identifiable risks can be handled with money.

Philosophiae Doctor - PhD
Recently, massive migration of enterprise applications to the cloud has been recorded in the Information Technology (IT) world. The number of cloud providers offering their services and the number of cloud customers interested in using such services is rapidly increasing. However, one of the challenges of cloud computing is Quality-of-Service management which denotes the level of performance, reliability, and availability offered by cloud service providers. Quality-of-Service is fundamental to cloud service providers who find the right tradeoff between Quality-of-Service levels and operational cost. In order to find out the optimal tradeoff, cloud service providers need to comply with service level agreements contracts which define an agreement between cloud service providers and cloud customers. Service level agreements are expressed in terms of quality of service (QoS) parameters such as availability, scalability performance and the service cost. On the other hand, if the cloud service provider violates the service level agreement contract, the cloud customer can file for damages and claims some penalties that can result in revenue losses, and probably detriment to the provider’s reputation. Thus, the goal of any cloud service provider is to meet the Service level agreements, while reducing the total cost of offering its services.

In cellular networks, channels should be allocated efficiently to support communication betweenmobile hosts. In addition, in cellular networks, base stations may fail. Therefore, designing a faulttolerantchannel allocation algorithm is important. That is, the algorithm should tolerate failuresof base stations. Many existing algorithms are neither fault-tolerant nor efficient in allocatingchannels.We propose channel allocation algorithms which are both fault-tolerant and efficient. In theproposed algorithms, to borrow a channel, a base station (or a cell) does not need to get channelusage information from all its interference neighbors. This makes the algorithms fault-tolerant,i.e., the algorithms can tolerate base station failures, and perform well in the presence of thesefailures.Channel pre-allocation has effect on the performance of a channel allocation algorithm. Thiseffect has not been studied quantitatively. We propose an adaptive channel allocation algorithmto study this effect. The algorithm allows a subset of channels to be pre-allocated to cells. Performanceevaluation indicates that a channel allocation algorithm benefits from pre-allocating allchannels to cells.Channel selection strategy also inuences the performance of a channel allocation algorithm.Given a set of channels to borrow, how a cell chooses a channel to borrow is called the channelselection problem. When choosing a channel to borrow, many algorithms proposed in the literaturedo not take into account the interference caused by borrowing the channel to the cells which havethe channel allocated to them. However, such interference should be considered; reducing suchinterference helps increase the reuse of the same channel, and hence improving channel utilization.We propose a channel selection algorithm taking such interference into account.Most channel allocation algorithms proposed in the literature are for traditional cellular networkswith static base stations and the neighborhood relationship among the base stations is fixed.Such algorithms are not applicable for cellular networks with mobile base stations. We proposea channel allocation algorithm for cellular networks with mobile base stations. The proposedalgorithm is both fault-tolerant and reuses channels efficiently.KEYWORDS: distributed channel allocation, resource planning, fault-tolerance, cellular networks,3-cell cluster model.

The symbiosis between plants of the legume family and nitrogen-fixing rhizobia underpins global food security. Legume crops are a major source of protein in human diets, either directly or indirectly as feed for livestock. Application of inoculant rhizobial strains is common practice in many areas, as plant growth is often nitrogen limited and the symbiosis can significantly enhance yields. However, rhizobial strains and outcomes of the symbiosis vary widely. This variation has also been studied by evolutionary biologists interested in the stability of mutualisms. They proposed that plants may prevent establishing symbioses with ineffective strains (partner choice), or provide them with fewer resources (sanctioning). I studied both mechanisms, combining modelling and experimental approaches. Mathematical modelling was used to predict how plants should allocate resources to maximise growth rates, depending on rhizobial nitrogen provision and carbon requirements and on soil nitrogen conditions. The use of marked mutant strains – easily distinguishable and differing in a single rhizobial characteristic – overcame previous experimental difficulties. It was found that pea (Pisum sativum L.) plants are not able to exert partner choice, but do sanction in a more complex way than was previously established. In line with model predictions, resources were preferentially allocated to the single – best available – strain, so that resources allocated to an intermediate-fixing strain depended on whether or not a strain providing more nitrogen was available. Contrary to model predictions, there was no indication of discrimination based on rhizobial carbon requirements. The results cannot be explained by resource allocation in proportion to nitrogen received, and indicate systemic integration of information from different nodules. I formulate a hypothesis about the underlying plant regulatory mechanisms, and discuss implications of the results for selecting inoculant strains and enhancing yields in the field. Future work will rely on further integration of theoretical and applied methods and perspectives.

Thesis (M.S. in Management) Naval Postgraduate School, December 1996.
Thesis advisor(s): Richard B. Doyle, Steven R Lamar. "December 1996." Includes bibliographical references (p. 147-152). Also available online.

Institutions of higher learning in South Africa should establish and sustain their own quality management systems. These systems should improve quality of the core business of higher education i.e. teaching and learning, research and community engagement. It should yield reliable information for internal planning as well as external monitoring purposes. The integration of quality management with planning and resource allocation within a framework of continuous improvement is viewed as fundamental elements for successful quality management of institutions of higher learning. A key assumption of this research is that quality management models should be underpinned by the systems theory in order to enhance the integration of quality management, planning and resource allocation on institutional strategic, tactical and operational levels. This study utilised the key elements and phases of the PDCA and ADRI models to develop a model for the integration of quality management, planning and resource allocation within a context of continuous improvement This model will be suitable for implementation by one of the institutions of higher learning in South Africa that fails, according to its latest HEQC audit to integrate quality management, planning and resource allocation. It offers also a conceptual framework for any institution of higher learning that fails to integrate quality management, planning and resource allocation.
Ph.D., Education, North-West University, Vaal Triangle Campus, 2010

This Thesis applies one of the most popular household models to the allocation of resources within poor rural households. Based on Browning and Goertz (2007) seminal Collective Household Model, the first Chapter conducts a literature review and derives conditions for identifying and testing the model. The next Chapter amends this model to evaluate efficiency of the intra-household allocation of male and female labour inputs in the domestic production of multiple crops. Using survey data from Uganda it is found that the division of labour between food and cash crops is made according to comparative advantage, but that Pareto improvements could be achieved by reallocating labour between male- and female-controlled plots. The final Chapter analyses the distribution of private consumption and leisure within rural couples in Tanzania. The findings provide limited support for the Collective Model, but are consistent with non-unitary household behaviour.

En cas de catastrophes importantes, telles qu’un tremblement de terre ou un incendie, l’efficacité des forces de la sécurité civile nécessite une bonne coordination des différents groupes d’intervention. Suivant la nature et l’importance du sinistre, l’infrastructure des moyens de communications classique peut être détruite. Les forces d’intervention ont donc besoin de nouveaux outils de communication dits réseaux de circonstance. Ces réseaux posent de nouveaux problèmes de routage, pour maintenir la connectivité, mais aussi d’allocation de ressources, particulièrement importante dans un contexte de sécurité où les communications doivent être garanties. Dans une première partie, nous avons abordé la problématique de l’allocation de ressources dans les réseaux de circonstance utilisant le partage TDMA. Nos solutions visent une répartition équitable des canaux et prennent en compte une zone d’interférence double de celle de transmission.Evaluer de nouvelles politiques dans des réseaux déployés sur des scènes de catastrophe nécessite de nouveaux modèles de mobilité. Nous avons donc également développé un nouveau modèle de mobilité spécifique au déplacement des équipes de la sécurité civile
When a major disaster occurs, such as an earthquake or fire, the efficiency of the rescue workers depends of the coordination between the different emergency teams. This coordination needs reliable communication equipments. In such a situation, however, the infrastructure for wireless communication is generally destroyed or unusable. It is therefore necessary to find adapted communication tools for the rescue workers known as opportunistic networks. These networks pose new challenging problems such as, for instance, resource allocation which is particularly important for the QoS satisfaction. In the first part of our thesis, we addressed the problem of resource allocation in ad hoc networks using the TDMA access mechanism. Our solutions aim to perform a fair distribution of channels and take into account an interference area twice as large as the transmission range. Evaluation of new policies for opportunistic networks deployed in disaster areas requires new mobility models. We developed a novel mobility model dedicated to the movement of rescue workers. Our model includes the group mobility and some characteristics of human mobility. It also incorporates a mechanism to circumvent obstacles presents in the simulation area

Increasingly tighter budgets, changes in government role/function, declines in staff resources, and demands for increased accountability in the transportation field have brought unprecedented challenges for state transportation officials at all management levels. Systematic methodologies for effective management of a specific type of infrastructure (e.g., pavement and bridges) as well as for holistically managing all types of infrastructure assets are being developed to approach these challenges. In particular, the intrinsic characteristics of highway system make the use of multi-objective optimization techniques particularly attractive for managing highway assets. Recognizing the need for effective tradeoff tools and the limitations of state-of-practice analytical models and tools in highway asset management, the main objective of this dissertation was to develop a performance-based asset management framework that uses multi-objective optimization techniques and consists of stand-alone but logically interconnected optimization models for different management levels. Based on a critical review of popular multi-objective optimization techniques and their applications in highway asset management, a synergistic integration of complementary multi-criteria optimization techniques is recommended for the development of practical and efficient decision-supporting tools. Accordingly, the dissertation first proposes and implements a probabilistic multi-objective model for performance-based pavement preservation programming that uses the weighting sum method and chance constraints. This model can handle multiple incommensurable and conflicting objectives while considering probabilistic constraints related to the available budget over the planning horizon, but is found more suitable to problems with small number of objective functions due to its computational intensity. To enhance the above model, a hybrid model that requires less computing time and systematically captures the decision maker's preferences on multiple objectives is developed by combining the analytic hierarchy process and goal programming. This model is further extended to also capture the relative importance existent within optimization constraints to be suitable for allocations of funding across multiple districts for a decentralized state department of transportation. Finally, as a continuation of the above proposed models for the succeeding management level, a project selection model capable of incorporating qualitative factors (e.g. equity, user satisfaction) into the decision making is developed. This model combines k-means clustering, analytic hierarchy process and integer linear programming. All the models are logically interconnected in a comprehensive resource allocation framework. Their feasibility, practicality and potential benefits are illustrated through various case studies and recommendations for further developments are provided.
Ph. D.

Thesis (DPhill (Social Work))—University of Stellenbosch, 2005.
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.

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.

Le Cloud Computing est devenu un moyen largement utilisé pour l'interrogation de bases de données. Les fournisseurs de cloud actuels proposent une variété de services implémentés sur des architectures parallèles. Les objectifs de performances et les éventuelles pénalités dans le cas de violation sont établis au préalable dans un contrat appelé Service-Level Agreement (SLA). Le but du fournisseur est de maximiser son bénéfice tout en respectant les besoins des locataires. Avant la naissance des systèmes cloud, plusieurs travaux ont considéré le problème d'allocation de ressources pour l'interrogation de bases de données sur des architectures parallèles. Le plan d'exécution de chaque requête est un graphe de tâches dépendantes. L'expression "allocation de ressources" dans ces travaux sous-entend souvent le placement des tâches sur les ressources disponibles et aussi leur ordonnancement qui tient compte des liens de dépendance. Le but consistait principalement à minimiser le temps d'exécution de requêtes et maximiser l'utilisation de ressources. Par contre, dans le cloud ce but ne garantit pas nécessairement le meilleur bénéfice économique pour le fournisseur. Afin de maximiser le bénéfice et satisfaire les besoins des locataires, il est essentiel d'inclure le modèle économique et les SLAs dans le processus d'allocation de ressources. En effet, les besoins des locataires en terme de performances sont différents, il serait donc intéressant d'allouer les ressources d'une façon qui favorise les locataires les plus exigeants en assurant quand même une certaine qualité de service pour les locataires les moins exigeants. De plus, dans le cloud le nombre de ressources attribuées peut augmenter/diminuer selon la demande (élasticité) et le coût monétaire dépend du nombre de ressources attribuées, il devient donc intéressant de mettre en place un mécanisme pour choisir automatiquement le moment adéquat pour ajouter ou supprimer des ressources en fonction de la charge (dimensionnement automatique). Nous nous intéressons dans le cadre de cette thèse à la conception de méthodes d'allocation de ressources élastique pour les services d'interrogation de bases de données dans le cloud : (1) une méthode d'allocation de ressources statique en deux phases pour assurer un bon compromis entre le bénéfice du fournisseur et la satisfaction des locataires, tout en garantissant un coût d'allocation raisonnable, (2) une méthode de réallocation de ressources dirigée par les SLAs pour limiter l'impact des erreurs d'estimation sur le bénéfice et (3) une méthode de dimensionnement automatique basée sur l'apprentissage par renforcement qui répond aux spécificités de l'interrogation de bases de données. Afin d'évaluer nos contributions, nous avons implémenté nos méthodes dans un environnement cloud simulé et nous les avons comparées à des méthodes de l'état de l'art en terme de coût monétaire de l'exécution de requêtes ainsi que le coût d'allocation
Cloud computing has become a widely used way to query databases. Today's cloud providers offer a variety of services implemented on parallel architectures. Performance targets and possible penalties in case of violation are established in advance in a contract called Service-Level Agreement (SLA). The provider's goal is to maximize its benefit while respecting the needs of tenants. Before the birth of cloud systems, several studies considered the problem of resource allocation for database querying in parallel architectures. The execution plan for each query is a graph of dependent tasks. The expression "Resource allocation" in this context often implies the placement of tasks within available resources and also their scheduling that takes into account dependencies between tasks. The main goal was to minimize query execution time and maximize the use of resources. However, this goal does not necessarily guarantee the best economic benefit for the provider in the cloud. In order to maximize the provider's benefit and meet the needs of tenants, it is important to include the economic model and SLAs in the resource allocation process. Indeed, the needs of tenants in terms of performance are different, so it would be interesting to allocate resources in a way that favors the most demanding tenants and ensure an acceptable quality of service for the least demanding tenants. In addition, in the cloud the number of assigned resources can increase/decrease according to demand (elasticity) and the monetary cost depends on the number of assigned resources, so it would be interesting to set up a mechanism to automatically choose the right moment to add or remove resources according to the load (auto-scaling). In this thesis, we are interested in designing elastic resource allocation methods for database queries in the cloud. This solution includes: (1) a static two-phase resource allocation method to ensure a good compromise between provider benefit and tenant satisfaction, while ensuring a reasonable allocation cost, (2) an SLA-driven resource reallocation to limit the impact of estimation errors on the benefit and (3) an auto-scaling method based on reinforcement learning that meet the specificities of database queries. In order to evaluate our contributions, we have implemented our methods in a simulated cloud environment and compared them with state-of-the-art methods in terms of monetary cost of the execution of queries as well as the allocation cost

While costing methods have developed over time, they are often static in nature and ill-suited to the dynamic nature of production lines. Static costing systems are often developed for long-term analysis. Due to this, they lack the ability to aid short-term decision-making. In addition, the use of averaged data prohibits a static costing system from accurately tracing the cost effects of changing system behavior like random downtime events. A dynamic costing system, however, can capture the cost effects of changing system behavior in a manner that can aid short-term operational management. The proposed methodology is a dynamic activity-based costing method that relies on real-time production line data to track costs, specifically the added costs of unused capacity and downtime events. The methodology aims to trace these costs to responsible cost centers on the production line to give a better representation of the total cost of production, specifically in regards to normal production costs, added downtime costs, and added costs from unused capacity. In addition to monetary costs, the methodology provides a framework for tracking environmental costs, such as energy use, in order to aid plant managers with determining the environmental impact of their operations. The methodology addresses a gap between activity-based costing and downtime costing by combining the two under a single methodology. It traces both monetary and environmental costs to cost centers on the manufacturing line to aid continuous improvement efforts and the allocation of resources. By using real-time data, the methodology alerts management to changing system performance in a shorter time frame than static costing systems. The methodology will be shown in a case study of an automotive assembly plant. The case study will model the resource use of an automotive paint shop and trace this resource use to line segments in order to highlight areas of possible improvement.

The pervasive availability of streaming data from various sources is driving todays’ enterprises to acquire low-latency big data streaming applications (BDSAs) for extracting useful information. In parallel, recent advances in technology have made it easier to collect, process and store these data streams in the cloud. For most enterprises, gaining insights from big data is immensely important for maintaining competitive advantage. However, majority of enterprises have difficulty managing the multitude of BDSAs and the complex issues cloud technologies present, giving rise to the incorporation of cloud service brokers (CSBs). Generally, the main objective of the CSB is to maintain the heterogeneous quality of service (QoS) of BDSAs while minimizing costs. To achieve this goal, the cloud, although with many desirable features, exhibits major challenges — resource prediction and resource allocation — for CSBs. First, most stream processing systems allocate a fixed amount of resources at runtime, which can lead to under- or over-provisioning as BDSA demands vary over time. Thus, obtaining optimal trade-off between QoS violation and cost requires accurate demand prediction methodology to prevent waste, degradation or shutdown of processing. Second, coordinating resource allocation and pricing decisions for self-interested BDSAs to achieve fairness and efficiency can be complex. This complexity is exacerbated with the recent introduction of containers. This dissertation addresses the cloud resource elasticity management issues for CSBs as follows: First, we provide two contributions to the resource prediction challenge; we propose a novel layered multi-dimensional hidden Markov model (LMD-HMM) framework for managing time-bounded BDSAs and a layered multi-dimensional hidden semi-Markov model (LMD-HSMM) to address unbounded BDSAs. Second, we present a container resource allocation mechanism (CRAM) for optimal workload distribution to meet the real-time demands of competing containerized BDSAs. We formulate the problem as an n-player non-cooperative game among a set of heterogeneous containerized BDSAs. Finally, we incorporate a dynamic incentive-compatible pricing scheme that coordinates the decisions of self-interested BDSAs to maximize the CSB’s surplus. Experimental results demonstrate the effectiveness of our approaches.

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IFAM - Instituto Federal de Educação, Ciência e Tecnologia do Amazonas
A responsabilidade de tomar decisões em si não é fácil, e quando está relacionada à gestão de recursos na área pública é uma tarefa ainda mais difícil, pois está ligada a um alto nível de complexidade. Neste trabalho, é apresentado um modelo computacional baseado em análise de decisão multicritério para a priorização da alocação de recursos financeiros para as comunidades ribeirinhas da região de Coari, Amazonas. Com o surgimento da Pesquisa Operacional, foi possível o desenvolvimento de métodos que auxiliam os tomadores de decisão no que se refere à avaliação e escolha em ambientes que envolvem multicritérios. É o caso da gestão pública, cuja decisão sobre a alocação de recursos passa pela análise de diversos critérios. As técnicas de decisão multicritério, aliadas às novas tecnologias de informação e comunicação, possibilitam novas formas de conhecimento e maior qualidade em diversos serviços. O emprego destas tecnologias no desenvolvimento de ferramentas de auxílio à decisão para a alocação de recursos é de grande utilidade, tendo em vista a automação no processo de análise e rapidez na obtenção dos resultados, possibilitando agilidade na tomada de decisão. Neste trabalho, é desenvolvido um modelo computacional baseado na técnica de Auxílio à Decisão Multicritério para ajudar na alocação de recursos públicos em comunidades ribeirinhas do Amazonas. O modelo emprega a técnica TOPSIS de análise multicritério com o intuito de obter um ranking das comunidades, para assim indicar aquela com maior grau de prioridade para receber a alocação de recursos públicos. Os experimentos foram realizados assumindo um conjunto de seis critérios empregados na ordenação de oito regiões de comunidades ribeirinhas. No estudo realizado, a lista de priorização indicou a região de comunidades do Baixo Solimões como a prioritária para a alocação de recursos públicos e a robustez da priorização obtida na aplicação efetuada foi avaliada através da realização de uma análise de sensibilidade.
The responsibility of making decisions itself is not easy, and when it is related to the management of resources in the public sector is an even more difficult task, because it is linked to a high level of complexity. In this paper, we present a computational model based on multi-criteria decision analysis to prioritize the allocation of financial resources to the coastal communities of Coari region of Amazonas. With the emergence of Operational Research, development methods was possible that assist decision makers with regard to the evaluation and choice in environments that involve advanced. This is the case of public administration, whose decision on the allocation of resources involves the analysis of various criteria. The techniques of multi-criteria decision, combined with the new technologies of information and communication, enable new forms of knowledge and higher quality in different services. The use of these technologies in the development of the decision support tools for the allocation of resources is useful in view of automation in the process of analysis and speed in obtaining results, enabling agility in decision making. In this work, we developed a computational model based on the technique of Aid to Decision Multicriteria to assist in the allocation of public resources in riverine communities of Amazonas. The model uses the TOPSIS technique of multi-criteria analysis in order to obtain a ranking of the communities, so as to indicate that more priority to receive the allocation of public resources. The experiments were performed assuming a set of six criteria used in the ordination of eight regions of riverside communities. In the study, the list of priority indicated the region of the Lower Solimões communities as a priority for the allocation of public resources and the robustness of the obtained priority in the application made was assessed by performing a sensitivity analysis.

Les conséquences des chocs économiques négatifs sur les ménages ont été documentés extensivement, mais on en sait beaucoup moins sur la manière dont ces chocs sont transmis aux individus à travers la médiation du ménage. Le ménage contribue-il à modérer l'effet des chocs négatifs ? Dans quelle mesure le choc économique pèse-t-il dans la négociation familiale ? À partir de données sur la crise économique argentine de 2001, je montre d'abord que les femmes en couple ont une plus grande probabilité de devenir actives si leur mari a fait l'expérience d'un choc de revenu. Ensuite, je montre que le cycle économique importe dans les décisions d'investissement en capital humain. Sur le long terme, les profils de salaire et d'employabilité des hommes argentins sont affectés de manière persistante par les conditions économiques initiales au moment de l'obtention du diplôme. Enfin, je considère la dimension “man-cession” de la crise économique de 2009 en Espagne et montre que la part des ressources du ménage reçues par les femmes pour leur consommation privée augmente avec la diminution de l'écart des taux de chômage hommes-femmes, confortant l'hypothèse que les chocs négatifs modifient le pouvoir de négociation des individus au sein du ménage
The consequences of adverse aggregate shocks on households have been repeatedly documented, but far less has been said on the way they are passed over to individuals through the mediation of the household. Does the household contribute in mitigating the effects? Or does the economic shock rather invite itself at the family negociating table? Using the Argentine 2001 economic crisis as a natural experiment, I first show that married women are more likely to enter the labor market if their husband experienced a loss in income, giving credit to the insurance mechanism. Then, I show that the business cycle matters for investments in education, and that long run labor outcomes of Argentine men are persistently affected by the initial conditions upon graduation. Finally, I consider the “Mancession” dimension of the Great Recession in Spain and demonstrate that the resource share accruing to wives for own consumption increases together with the decreasing unemployment gap, which comes in support to the bargaining hypothesis

Thesis (Ph. D.) -- University of Maryland, College Park, 2005.
Thesis research directed by: Economics. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.

京都大学
0048
新制・課程博士
博士(情報学)
甲第22809号
情博第739号
新制||情||126(附属図書館)
京都大学大学院情報学研究科通信情報システム専攻
(主査)教授 大木 英司, 教授 守倉 正博, 教授 原田 博司
学位規則第4条第1項該当
Doctor of Informatics
Kyoto University
DFAM

La tesis presenta una aproximació a un conjunt de tècniques per permetre l'extensió de les capacitats computacionals, sota demanada, en comunitats formades per usuaris d'Internet que volen agregar els seus recursos per aconseguir una finalitat comuna. Aquest tipus de comunitats, emergeixen com a noves formes d'organització gràcies a l'increment de les capacitats computacionals i l'ampla de banda. La computació voluntaria com la que es dona en sistemes com SETI@home, Grids col.laboratius com OurGrid o LaCOLLA, Ad-hoc i Grids d'igual a igual com P-Grid o X-Grid d'Apple, Grids Oberts com els adreçats per SORMA o Grid4All i moltes d'altres formes de computació Grid basades en agrupació de recursos en forma d'Organitzacions Virtuals són l'objectiu d'aquest treball. Aquests sistems es caracteritzen pel propòsit dels seus participants, és a dir, dur a terme un objectiu comú fent ús de l'agregació dels sesus propis recursos. Els sistemes esmentats, contrariament als sistemes Grid d'alt rendiment computacional, són oberts a nous participants fet que els converteix en escenaris inpredictibles, dinàmics i on els recuros poden connectar-se i desconnectar-se de forma espontànea. Mentre que l'aspecte crític dels Grids d'altes prestacions és el rendiment computacional, l'estabilitat i la disponibilitat són els aspectes més importants en els sistemes adrec cats en aquest treball. La tesis homogeinitza els conceptes dels paradigmes anteriors sota el nom de Sistemes Contributius, nom que és usat al llarg de la dissertació per referir-nos a sistemes en els quals els seus usuaris fan contribució dels seus recursos per tal que aquest siguin usats de forma col.lectiva i axií aconseguir un objectiu comú. L'expansió de recursos en els Sistemes Contributius és una funcionalitat requerida per tal de augmentar les limitades capacitats computacionals dels grups col.laboratius formats de forma ad-hoc. Sobretot en moments puntuals quan els recursos necessaris són majors que els disponibles en el grup. Quatre aspectes s'adressen al llarg de la dissertació. Primer, les propietats i principals applicacions dels Sistemes Contributius són identificades, així com es motiva la necessitat d'infraestructures que permetin l'expansió de recursos computacionals sota demanda. Aquestes idees van en la direcció de l'Utility Computing, emergents línies de negoci de les principals companyies de la IT. D'aquesta manera, la tesis proposa la provisió de recursos computacionals sota demanda a aquelles organitzacions que en necessitin, mitjanc cant l'agregació de recursos dels extrems d'Internet, ja siguin usuaris finals de la xarxa, altres organitzacions virtuals o proveidors de recursos. En aquest treball, l'assignació de recursos es gestionada per models de mercat ja que proveixen de mecanismes eficients i simples per gestionar l'assignació de recursos. Aquesta proposta aporta noves oportunitats als usuaris finals d'Internet per tal d'establir el seu negoci a la xarxa mitjanc cant la venda dels seus recursos no usats. A més a més aquest treball dona l'oportunitat a communitats petites a creixer i a portar capacitats de super-computació als usuaris finals d'Internet. En segon lloc, la tesis descriu semànticament els recursos computacionals per tal de constru"ir una base comú de coneixement sobre els recursos d'Internet. La descripció semàntica dels recursos permet un enteniment comú de la naturalesa dels recursos, permetent així l'agrupació i agregació de diferents tipus de tecnologíes mentre es mantenen la mateixa semàntica. Una base semàntica comú permet que aplicacions i sistemes de gestió de recursos siguin independents de la naturalesa real dels recursos. En aquest treball considerem com a aspecte fonamental aillar la gestió dels recursos de la seva naturalesa específica. La descripció semàntica a més permet el desenvolupament de especificacions genèriques que ens permeten definir els requeriments dels usuaris en sistemes d'assignació de recursos basats en mercats computacionals. Tercer, arquitectures que permeten l'expansió de recursos computacionals sota demanda en Sistemes Contributius són presentades. Aquestes arquitectures han estat especialment dissenyades per prove"ir de recursos computacionals mitjanc cant mercats a escenaris caracteritzats pel dinamisme, evolució i heterogene"itat dels seus recursos. L'arquitectura aporta les principals funcionalitats orientades a l'assignació de recursos mitjanc cant subhastes i permet a més a més l'execució d'aquests mercats sota demanda. Finalment, es presenta un mecanisme de mercat adaptat a l'assignació de recursos computacionals. Aquesta contribució es motiva pel fet que no existeix fins avui cap mecanisme que permeti l'assignació efficient de recursos computacionals en que la seva única diferència és la unitat de temps en la que s'ofereixen. La tesis construeix un camí per assolir l'expansió de recursos computacionals de forma flexible i decentralitzada en comunitats on els recursos són compartits pels seus participants. Aquest camí es construeix mitjanc cant l'anàlisis dels escenaris d'aplicació, l'estudi i definició de models semàntics que permeten la descripció dels recursos computacionals, proposant també arquitectures flexibles i configurables que permeten aconseguir l'expansió dels recursos computacionals sota demanda i proposant mecanismes de mercat adaptats a tal escenari.
The thesis presents an approach to on-demand capacity expansion in communities of Internet users that aggregate their resources to achieve a common objective. Such commu- nities are emerging as forms of organisation taking advantage of an increasing broadband access and computational capacity. Volunteer computing such as SETI@home, Collab- orative Grids such as OurGrid and LaCOLLA, Ad-hoc and Peer-to-Peer Grids, such as P-Grid and the XGrid project from Apple, Open Grids such as those addressed by SORMA and Grid4All and many other approaches of Grid Computing based on Virtual Organisa- tions are the focus of our work. These systems are characterised by the purpose of their participants, i.e. to achieve a common objective taking advantage of the aggregation of other resources. The cited systems, in contrast to high performance computing Grids, are open to new participants, which makes their behaviour unpredictable and dynamic, and resources are usually connected and disconnected spontaneously. While the critical aspect of high performance Grids is computational performance, stability and availability are the main issues for the systems addressed in this work. The thesis homogenises the concepts of those paradigms under the term Contributory System, which is used throughout the thesis to refer to the systems where users provide their resources to be used collectively to achieve a common objective. Resource expan- sion in Contributory Systems is required so as to increase the limited capacities of ad-hoc collaborative groups under unexpected load surges, temporary resource requirements or other policies defined by the objectives of the Virtual Organisation that they constitute. Four aspects are addressed by the dissertation. Firstly, it identifies the main properties and applications of Contributory Systems and motivates the need for infrastructures to enable on-demand resource expansion. This goes in the direction of Utility Computing trends which are main business lines for IT companies. Thus the thesis proposes the on-demand provision of idle resources from the extremes of the Internet, other Virtual Or- ganisations or Resource Providers to those organisations that have resource needs. In this work, resource allocation is handled by market models which provide efficient while simple mechanisms to mediate the allocation of resources. This proposal enables new emerging opportunities to Internet users to make their business on the Internet by selling their idle resources. Besides, this brings the opportunity to small communities to grow and to bring super-computing capacities to Internet end-users. Secondly, the thesis describes semantically Computational Resources so as to build a common knowledge about the Internets resources. The semantic description enables a common understanding of the nature of resources, permitting the pooling and aggrega- tion of distinct types of technologies while maintaining the same semantics. This makes applications and resource management frameworks independent of the real nature of the resources which we claim as a fundamental aspect to keep resource management indepen- dent of the dynamics and evolution of technology in computational environments, such as in Contributory Systems. A semantic description permits the development of generic specifications to provide bid and offer descriptions in computational markets. Thirdly, the architecture for on-demand resource expansion in Contributory Systems is presented. It has been designed to provide the main functionalities to on-demand provi- sion of resources through markets to scenarios characterized by dynamism, evolution and heterogeneity. The architecture provides the main market oriented functionalities and en- ables dynamic and on-demand execution of market mechanisms. Finally, a specific Grid-oriented market mechanism is presented. The approach is moti- vated due to the unsuitability of current auctions to efficiently allocate time-differentiated resources (usually provided by many different resource providers) such as most of the re- sources in a Contributory System. The thesis builds a roadmap to achieve flexible and decentralized resource expansion in communities where resources are shared by their participants by analysing the main scenarios where it can be applied, providing the semantics and specification to enable the description of the user's requirements, proposing a flexible and configurable architecture to deal with on-demand resource expansion in Virtual Organisations and proposing an specific mechanism adapted to trade computational resources.

The IEEE 802.16 standard popularly known as WiMAX is at the forefront of the technological drive. Achieving high system throughput in these networks is challenging due to interference which limits concurrent transmissions. In this thesis, we study routing and link scheduling inWiMAX mesh networks. We present simple joint routing and link scheduling algorithms that have outperformed most of the existing proposals in our experiments. Our session based routing and links scheduling produced results approximately 90% of a trivial lower bound. We also study the problem of quality of service (QoS) provisioning in WiMAX mesh networks. QoS has become an attractive area of study driven by the increasing demand for multimedia content delivered wirelessly. To accommodate the different applications, the IEEE 802.16 standard defines four classes of service. In this dissertation, we propose a comprehensive scheme consisting of routing, link scheduling, call admission control (CAC) and channel assignment that considers all classes of service. Much of the work in the literature considers each of these problems in isolation. Our routing schemes use a metric that combines interference and traffic load to compute routes for requests while our link scheduling ensures that the QoS requirements of admitted requests are strictly met. Results from our simulation indicate that our routing and link scheduling schemes significantly improve network performance when the network is congested.
ix, 77 leaves : ill. ; 29 cm

This dissertation consists of three chapters on the topic of intrahousehold resource allocation models. The first chapter tests the unitary and general collective models of intrahousehold resource allocation for various household compositions. I find that, for the quasi-quadratic Engel curve specification, the overall results support the previous findings in the literature that the unitary model fails to explain how resources are allocated for all household types. However, when using the QUAIDS specification, the results can reject the unitary model only for smaller-sized households. The general collective model, on the other hand, cannot be rejected in either quasi-quadratic or QUAIDS and not in any of the household compositions. Overall, the results support the general collective model of household behavior rather than the unitary model. The second chapter derives and tests restrictions imposed by the collective model for households with more than two decision-makers in the absence of price variation. It extends the two-decision-maker model in chapter one to derive the testable restrictions for households with multiple decision makers using unconditional demand systems. Moreover, for comparison, a particular type of demand system that is conditional on distribution factors is also estimated as an alternative way to test the collective model. The results show that neither unconditional nor conditional demand systems can reject Pareto efficiency. Therefore, both approaches provide consistent outcomes supporting the hypothesis that the multiple-decision-maker households in Thailand behave in the Pareto efficient manner predicted by the collective model. Finally, my third chapter attempts to examine how one can exploit household-level consumption data to recover information about individual household members for situations with no price variation. By combining consumption data from single and couple households, I am able to estimate the resource shares and indifference scales (a variation of the standard equivalence scales in the collective settings) for each household member via a system of Engel curves. The results show that, in Thailand, wives are likely to have higher resource shares than husbands in the married-couple households, while wives with higher education have the ability to extract more household resources. However, resource shares for wives are smaller for older-married compared to younger-married couples. Moreover, if a female were to live alone, she would need approximately three-quarters of the couple's income to reach the same indifference curve, and hence the same standard of living, that she would attain as a wife in the married-couple household.
ID: 030646226; System requirements: World Wide Web browser and PDF reader.; Mode of access: World Wide Web.; Thesis (Ph.D.)--University of Central Florida, 2011.; Includes bibliographical references (113-116).
Ph.D.
Doctorate
Economics
Business Administration
Economics

Cette thèse traite de quatre problèmes dans le contexte des grands systèmes distribués. Ce travail est motivé par les questions soulevées par l'expansion du Cloud Computing et des technologies associées. Le présent travail étudie l'efficacité de différents algorithmes d'allocation de ressources dans ce cadre. Les méthodes utilisées impliquent une analyse mathématique de plusieurs modèles stochastiques associés à ces réseaux. Le chapitre 1 fournit une introduction au sujet, ainsi qu'une présentation des principaux outils mathématiques utilisés dans les chapitres suivants. Le chapitre 2 présente un mécanisme de contrôle de congestion dans les services de Video on Demand fournissant des fichiers encodés dans diverses résolutions. On propose une politique selon laquelle le serveur ne livre la vidéo qu'à un débit minimal lorsque le taux d'occupation du serveur est supérieur à un certain seuil. La performance du système dans le cadre de cette politique est ensuite évaluée en fonction des taux de rejet et de dégradation. Les chapitres 3, 4 et 5 explorent les problèmes liés aux schémas de coopération entre centres de données (CD) situés à la périphérie du réseau. Dans le premier cas, on analyse une politique dans le contexte des services de cloud multi-ressources. Dans le second cas, les demandes arrivant à un CD encombré sont transmises à un CD voisin avec une probabilité donnée. Au troisième, les requêtes bloquées dans un CD sont transmises systématiquement à une autre où une politique de réservation (trunk) est introduite tel qu'une requête redirigée est acceptée seulement s'il y a un certain nombre minimum de serveurs libres dans ce CD
This PhD thesis investigates four problems in the context of Large Distributed Systems. This work is motivated by the questions arising with the expansion of Cloud Computing and related technologies. The present work investigates the efficiency of different resource allocation algorithms in this framework. The methods used involve a mathematical analysis of several stochastic models associated to these networks. Chapter 1 provides an introduction to the subject in general, as well as a presentation of the main mathematical tools used throughout the subsequent chapters. Chapter 2 presents a congestion control mechanism in Video on Demand services delivering files encoded in various resolutions. We propose a policy under which the server delivers the video only at minimal bit rate when the occupancy rate of the server is above a certain threshold. The performance of the system under this policy is then evaluated based on both the rejection and degradation rates. Chapters 3, 4 and 5 explore problems related to cooperation schemes between data centres on the edge of the network. In the first setting, we analyse a policy in the context of multi-resource cloud services. In second case, requests that arrive at a congested data centre are forwarded to a neighbouring data centre with some given probability. In the third case, requests blocked at one data centre are forwarded systematically to another where a trunk reservation policy is introduced such that a redirected request is accepted only if there are a certain minimum number of free servers at this data centre

Les organisations adoptent de plus en plus les Systèmes (PAIS) pour gérer leurs processus métiers basés sur les services en utilisant les modèles de processus appelés «modèles de processus métiers». Motivés par l’adaptation aux exigences commerciales et par la réduction des coûts de maintenance, les organisations externalisent leurs processus dans le Cloud Computing. Selon l'Institut NIST, Cloud Computing est un modèle qui permet aux fournisseurs de partager leurs ressources et aux utilisateurs d’y accéder de manière pratique et à la demande. Dans un tel environnement multi-tenant, l'utilisation de modèles de processus configurables permet aux fournisseurs de processus Cloud de fournir un processus personnalisable qui peut être configuré par différents tenants en fonction de leurs besoins.Un processus métier peut être spécifié par plusieurs perspectives tel que la perspective de flux de contrôle, la perspective des ressources, etc. Plusieurs approches ont été proposées au niveau des premières perspectives, notamment le flux de contrôle. Cependant, la perspective ressource, qui est d'une importance égale, était négligée et pas explicitement définie. D’un côté, la gestion de la perspective ressource spécifiquement l’allocation des ressources Cloud est un thème d’actualité qui implique plusieurs recherches. La modélisation et la configuration des ressources sont une tâche sensible nécessitant un travail intensif. Malgré l’existence de différentes approches, elles traitent principalement les ressources humaines plutôt que des ressources Cloud. D’un autre côté, malgré le fait que le concept des modèles de processus configurables est très complémentaire au Cloud, la manière dont comment les ressources sont configurées et intégrées est à peine manipulée. Les approches proposées travaillant sur l’extension de la configuration de ressources, ne couvrent pas les propriétés Cloud notamment l’élasticité et le partage.Pour répondre à ces lacunes, nous proposons une approche pour supporter la modélisation et la configuration de l’allocation des ressources Cloud dans les modèles de processus configurables. Nous visons à (1) définir une description unifiée et formelle pour la perspective ressource, (2) assurer une allocation de ressource correcte, sans conflits et optimisée, (3) Aider les fournisseurs de processus à concevoir leur allocation de ressources configurable de manière fine afin d'éviter des résultats complexes et importants, et (4) Optimiser la sélection des ressources Cloud par rapport aux exigences liées aux propriétés Cloud (élasticité et partage) et propriétés QoS.Pour ce faire, nous proposons d'abord un cadre sémantique pour une description de ressources sémantiquement enrichies dans les processus métiers visant à formaliser les ressources Cloud consommées à l'aide d'une base de connaissances partagée. Ensuite, nous nous basons sur les processus métiers sociales pour fournir des stratégies afin d'assurer une allocation de ressources contrôlée sans conflits en termes de ressources. Par la suite, nous proposons une nouvelle approche qui étend les modèles de processus configurables pour permettre une allocation de ressources Cloud configurable. Notre objectif est de déplacer l'allocation de ressources Cloud du côté des tenants vers le côté du fournisseur de processus Cloud pour une gestion centralisée des ressources. Après, nous proposons des approches génétiques qui visent à choisir une configuration optimale des ressources d'une manière efficace sur le plan énergétique en améliorant les propriétés QoS.Afin de montrer l'efficacité de nos propositions, nous avons développé concrètement (1) une série de preuves de concepts, en tant que partie de validation, pour aider à concevoir des modèles de processus et remplir une base de connaissances de modèles de processus hétérogènes avec des ressources Cloud et (2) ont effectué des expériences sur des modèles de processus réels à partir de grands ensembles de données
Organizations are recently more and more adopting Process-Aware Information Systems (PAIS) for managing their service-based processes using process models referred to as business process models. Motivated by adapting to the rapid changing business requirements and reducing maintenance costs, organizations are outsourcing their processes in an important infrastructure which is Cloud Computing. According to the NIST Institute, Cloud Computing is a model that enables providers sharing their computing resources (e.g., networks, applications, and storage) and users accessing them in convenient and on-demand way with a minimal management effort. In such a multi-tenant environment, using configurable process models allows a Cloud process provider to deliver a customizable process that can be configured by different tenants according to their needs.A business process could be specified from various perspectives such as the control-flow perspective, the organizational perspective, the resource perspective, etc. Several approaches have been correctly proposed at the level of the first perspectives, in particular the control-flow, i.e., the temporal ordering of the process activities. Nevertheless, the resource perspective, which is of equal importance, has been neglected and poorly operated. The management of the resource perspective especially the Cloud resource allocation in business processes is a current interesting topic that increasingly involves many researches in both academics and industry. The design and configuration of resources are undoubtedly sensitive and labor-intensive task. On the one hand, the resource perspective in process models is not explicitly defined. Although many proposals exist in the literature, they all targeted human resources rather than Cloud resources. On the other hand, despite of the fact that the concept of configurable process models is highly complementary to Cloud Computing, the way in how resources can be configured and integrated is hardly handled. The few proposals, which have been suggested on extending configuration to resources, do not cover required Cloud properties such as elasticity or multi-tenancy.To address these limitations, we propose an approach for supporting the design and configuration of Cloud resource Allocation in configurable business process models. We target to (1) define a unified and formal description for the resource perspective, (2) ensure a correct, free-of-conflict and optimized use of Cloud resource consumption, (3) assist process providers to design their configurable resource allocation in a fine-grained way to avoid complex and large results, and (4) optimize the selection of Cloud resources with respect to the requirements related to Cloud properties (elasticity and shareability) and QoS properties.To do so, we first suggest a semantic framework for a semantically-enriched resource description in business processes aiming at formalizing the consumed Cloud resources using a shared knowledge base. Then, we build upon social business processes to provide strategies in order to ensure a controlled resource allocation without conflicts in terms of resources. Next, we propose a novel approach that extends configurable process models to permit a configurable Cloud resource allocation. Our purpose is to shift the Cloud resource allocation from the tenant side to the Cloud process provider side for a centralized resource management. Afterwards, we propose genetic-based approaches that aim at selecting optimal resource configuration in an energy efficient manner and to improve non-functional properties.In order to show the effectiveness of our proposals, we concretely developed (i) a set of proof of concepts, as a validation part, to assist the design of process models and populate a knowledge base of heterogeneous process models with Cloud resources, and (ii) performed experiments on real process models from large datasets

Tato práce se zabývá technologií Multiprotocol Label Switching a to zejména moderními metodami, které je možné použít v rámci této technolologie. Jako příklad lze uvést využití podpory kvality služeb při směrování. V práci jsou navrhnuty a simulovány různé topologie a scénáře, které ověřují možnosti využití MPLS v podpoře kvality služeb.

碩士
國立雲林科技大學
資訊管理系碩士班
101
Revenue management (RM) is one way to enhance the amount of revenue in IaaS cloud computing service. This study uses resource allocation and overbooking models from RM to appropriately allocate resources of reservations and manage cancellations and no-shows of reservations in IaaS service in order to increase revenues and improve resource utilization. With overbooking, the resource providers can minimize the loss of revenue and enhance the resource utilization. To efficiently manage resources and find an ideal limit that exceeds the maximum capacity, this study integrates the dynamic Expected Marginal Seating (Resource) Revenue (EMSR) model with the overbooking model for optimizing revenue. In testing process, the data is created with demand scenario by simulation. The result of the simulate study shows that using overbooking can increase the total revenue by up to 8%-11%, and the model in this study is verified that has better performance than traditional nested model. The findings of the study provide practical strategies to how IaaS providers manage bookings and control the number of overbooking so as to improve their revenues and the competitive advantage.

Subcontractors perform the majority of the work on commercial construction projects. However, only limited research has focused on subcontractors’ practical needs. In response, this research discovered and documented subcontractor needs through data collections and extended these findings with development of an information model and tool. This research significantly enlarges detailed understanding of subcontractor management practices, in particular around resource allocation across multiple projects. While existing research has shown the importance of multi-project management, exploration of details of this process has largely been limited to overviews of policies. Rich details that allow for specific critiques of existing methods and tools have been missing. This research provides such details, including specific limitations and recommendations to existing information standards, commercial applications, and assignment algorithms. In particular, contributions of this research focus on support for what-if analysis under extreme frequency of resource reallocation, a limitation of existing tools and methods that make them unsuitable for most subcontractors.
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Force deployment and optimal resource allocation has been an area of considerable research interest in conventional warfare. In the modern scenario, with significant advances in technology related to communication and computation, sophisticated decision-making in these situations has become feasible. This has generated renewed interest in formulating decision-making problems in these areas and seeking optimal solutions to them. This thesis addresses one such problem in which the defending forces need to optimally Partition their resources between several attacking forces of differing strengths. The basic model considered for resource allocation is Lanchester attrition models. Lanchester models are deterministic differential equations that model attrition to forces in convict. In this thesis we address a resource allocation problem where the resource allocation is done using different approaches. First, we developed a (2,1) model using the Lanchester square law model for attrition. For this model we assumed that the attacking force consists of two types of forces and the defending force consists of only one type of force. The objective is to optimally partition the defending force against the two attacking forces so as to maximize the surviving defending force strength and to minimize the attacking force strength. The objective function considered in this thesis is the weighted sum of the surviving defending force strength and the destroyed attacking force strength. We considered a resource allocation problem in which allocation of resources are done using four different approaches. The simplest is the case when allocation is done initially and no further action is taken Iv Abstract v (Time Zero Allocation (TZA)). For the TZA allocation scheme, when any of attacking forces gets destroyed, the corresponding defending force which was engaging that attacking force will stop interacting further. This situation rarely happens in reality. Hence to make this scenario more realistic, we considered another allocation scheme in which allocation is followed by redistribution of resources depending on certain decisive events (Time Zero Allocation with Redistribution (TZAR)). In TZA and TZAR schemes, the allocation of defending force is done only at the initial time. Deviating from this assumption, we considered another allocation scheme in which a constant allocation ratio is used continuously over time till the end of the convict (Continuous Constant Allocation (CCA). To account for the redistribution of resources we extended this allocation scheme to the case in which continuous constant allocation is followed by redistribution of the resources (Continuous Constant Allocation with Redistribution (CCAR)). In each of these formulations we define the conditions for an optimal resource partitioning and allocation. We were able to obtain analytical expression for resource partitioning in almost all of these cases. Next, in order to consider situations in which area fire is required, we developed a (2,1) model using Lanchester linear law model for attrition. Here we considered a resource allocation problem in which the resource allocation is done using ideas similar to the square law case. In the Linear law, the resources will get destroyed completely only at infinite time, hence a situation for redistribution of resources does not arise for this law. We considered Time Zero Allocation and Continuous Constant Allocation schemes for this law. We obtained analytical results for the TZA scheme. For the CCA scheme, closed form solutions are difficult to obtain but numerical solutions were obtained. The above schemes were extended to an (n, 1) model for resource allocation using Lanchester square and linear laws. Here the defending forces have to determine an optimal partitioning of available resources to counter attacks from an adversary from n different fronts. For the square law model, we considered both TZA and CCA schemes for resource allocation. As the number of force types increases, the equations becomes much more complicated and the analytical solutions are difficult to obtain. We were able to obtain analytical solutions for some of the situations that occurs during the conflict. For the linear law, we considered only the TZA scheme since, even for the simpler (2,1) model, the analytical solutions are difficult to obtain for the CCA scheme. The resource allocation strategies developed in this thesis contribute to the growing research in the field of conflicts. The thesis concludes with a discussion on some future Extensions of this work.

碩士
東海大學
工業工程學系
89
Due to the changing environment, the products in electronics industry vary enormously. The common problems faced with the electronics industry as well as other industries in Taiwan included unpredictable demand, different lead time of various material, tight delivery schedule and constant changing of production plan. Electronics industry needs to catch up with the market trend, so that it can responds to customer needs quickly and to overcome the problems caused by the over-centralized industries, products and markets. Besides, traditional production planning method (e.g., MRP) cannot fulfill the requirements of effective production planning. Therefore, Advanced Planning and Scheduling (APS) system is promoted to solve the complex problems that planner encounter in production planning. Resource allocation is the core of APS, it can provide planners the material allocation reference and reduce inventory costs between forcasting order and customer order. In this thesis, a genetic algorithm-based resource allocation model for electronics industry is introduced. The model aims to solve ignoring costs for material allocation by “heuristic rule”. It measures costs such as supply order movement cost, and provides a decision suggestion for planners to cancel or change order. Finally, the model developed in this research is applied to a electronics industry to test it’s applicability in practice.

The three essays that comprise this thesis address the behavioral factors that impact resource allocation, more specifically trade and Foreign Direct Investment (FDI), around the globe. The first essay analyses the impact of language similarity on trade, measuring the effect on specific types of products. It extends earlier research on common language network externalities by measuring language similarity effect on bilateral trade from the point of view of the 10 most influential global languages. The findings provide evidence that the impact of language similarity is greater than that of language commonality, and both have a significant impact on bilateral trade. The results also show that language effect on trade varies within the 10 languages, and that this impact is product-specific: culturally sensitive products benefit from a greater language effect. The second essay is a macro level study of foreign direct investment (FDI). It uses an extended gravity model, data spanning 12 years (2000–2012), to shed new light on the impact on FDI of linguistic and technological similarities between countries. The model includes technological commonality, as measured by the aggregate production of intellectual property, at the country level. An analysis of 71 309 pairs of FDI relationships showed that language is positively associated with a high level of FDI. Technological differences do impede the flow of FDI between countries, and information flow is crucial for large flows of FDI. Information flow diminishes the negative impact of distance. The results also show different attitudes toward investment among high income and low income countries’ multinational corporations (MNCs). The third essay address Chief Executive Officer’s (CEO’s) demographic characteristics (e.g. age, education) which impact greenfield investment location decisions. Using a hierarchical model (e.g. binomial and linear), data spanning 10 years (2003–2012), the analysis of 49 138 global firm-level greenfield investments shows that CEO’s level of education is crucial to the decision of which country to select and the amount invested. The more educated a CEO is the more likely to invest in developing countries. The results also show that CEOs from developing and emerging countries (DECs) are more risk-prone than their peers from developed countries. They are also more likely to invest in countries considered risky. In addition, the results show that CEOs’ power is associated with less risky choices, that is, the more powerful a CEOs the more likely to invest in developed markets.
Os três artigos que compõem esta tese analisam os factores “comportamentais” que influenciam a alocação de recursos (e.g., comércio e investimento directo estrangeiro (IDE)) a nível global. O primeiro artigo analisa o efeito da similaridade linguística no comércio mundial e em particular em certos produtos. Esta análise é feita do ponto de vista das 10 línguas mais influentes a nível global. Os resultados desta análise oferecem uma interpretação inequívoca sobre o positivo efeito da língua no comércio. E ainda nos permitiu aferir da superioridade da similaridade linguística sobre a língua comum. Os resultados também demonstram que o efeito da língua é diferenciado entre as 10 línguas globalmente mais influentes e que este impacto é específico a certos produtos. Também verificamos que os produtos “culturais” são mais sensíveis ao efeito da língua. O segundo artigo é uma análise a nível macro do IDE. Para a análise referida utilizamos o modelo gravitacional, dados de 2000 – 2012 para analisar o efeito da assimetria de informação, similaridade linguística e tecnológica. Para índice de similaridade tecnológica utilizamos dados de propriedade intelectual a nível do país. A análise de 71309 pares de IDE entre países revelou o efeito positivo da língua sobre IDE. Verificamos que a diferença tecnológica impede o elevado fluxo de IDE e que o fluxo de informação é crucial para um elevado nível de IDE. Mais, verificamos que elevado fluxo de informação diminui o efeito negativo da distância. Ainda verificamos que a atitude em relação ao investimento varia consoante o nível de recursos dos países de origem. O terceiro artigo analisa o impacto das características demográficas dos gestores sob a decisão de IDE (i.e. greenfield). Usando modelos hierárquicos, dados de 2003 – 2012, a análise de 49138 dados de greenfield empresarial revela que o nível de educação dos gestores determina a escolha do país e o montante a investir. Também verificamos que quanto mais educado o gestor mais provável é investimentos nos países emergentes e em vias de desenvolvimento. Mais, também verificamos que os gestores originários dos países emergentes e em vias de desenvolvimento assumem mais riscos, i.e., é mais provável investirem em países emergentes ou em vias de desenvolvimento. Também verificamos que os gestores mais poderosos tendem a ter uma atitude mais conservador e assumir menos riscos.

博士
國立臺灣科技大學
電機工程系
87
This dissertation presents an object-oriented model to handle the temporal relationship for all of the multimedia objects at the presentation platform. Synchronization of the composite media objects is achieved by ensuring that all objects presented in the upcoming "manageable" period must be ready for execution. To this end, the nature of overlays is first examined for various types of objects. Critical overlaps which are crucial in synchronization are also defined. The objective of synchronization is to ensure that the media objects can be initiated precisely at the critical point of the corresponding critical overlap. The concept of manageable presentation interval is introduced and the irreducible media group is defined. Accordingly, a new model called group cascade object composition Petri-net (GCOCPN) is then proposed to facilitate partition of a presentation program of a distributed multimedia system into manageable irreducible media groups so that the multimedia information can be presented by the specific QoS requirement. The relation among buffer occupancy at the presentation platform, network bandwidth and objects pre-fetch time is also examined. Finally, a proposed resource allocation algorithm based on the upper bound of available system buffer capacity is proposed.

碩士
國立交通大學
工業工程與管理系所
103
For a public or private sector, the central decision-maker (CDM) governs a set of homogenous subordinates, decision-making units, DMUs. DMUs consume a set of input resources to produce a set of outputs. To improve the whole sector’s aggregate performance, CDM would allocate its resources and products among the DMUs. There are several literatures provide mathematical models to deal with the problem under their specific conditions, respectively. The current research based on virtual-gap-measurement (VGM) model and develops a new model under general conditions to have better solutions. We employ a numerical example to the models in literatures. The comparisons between our model and the others on efficiencies and slacks indicate our model outperforms the others.

博士
國立交通大學
科技管理研究所
96
The scale of war has been changed from large to small. The national defense department develops a new policy to meet the changes of the modern world. Meanwhile, the national defense budget of R.O.C. is not able to cover the needs. Therefore military developments are limited by the budget shortage. Consequently, the optimization of the resources allocation is an important issue. This research develops a policy to distribute the limited budget by considering the defense budget based on three items namely, personnel, maintenance, operating cost and the military investments using the bilevel programming to develop an optimal policy for the distribution of national defense budget. The bilevel model is solved by considering the history data of the national defense budget distribution to test the accuracy of the model. This bilevel model considers the maximization of the overall value of budget distribution under the idea of minimizing the difference of the ration of funded amount over request amount among the requesting units.