Tesi sul tema "Resource allocation"
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AuYoung, Alvin. "Practical market-based resource allocation". Diss., [La Jolla] : University of California, San Diego, 2010. http://wwwlib.umi.com/cr/ucsd/fullcit?p3397175.
Testo completoTitle from first page of PDF file (viewed March 29, 2010). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 146-155).
Choueiry, Berthe Y. Choueiry Berthe Yazid. "Abstraction methods for resource allocation /". [S.l.] : [s.n.], 1994. http://library.epfl.ch/theses/?nr=1292.
Testo completoMuñoz, i. Solà Víctor. "Robustness on resource allocation problems". Doctoral thesis, Universitat de Girona, 2011. http://hdl.handle.net/10803/7753.
Testo completoAquesta tesi se centra en l'elaboració de tècniques que consideren la incertesa alhora de cercar solucions robustes, és a dir solucions que puguin continuar essent vàlides encara que hi hagi canvis en l'entorn. Particularment, introduïm el concepte de robustesa basat en reparabilitat, on una solució robusta és una que pot ser reparada fàcilment en cas que hi hagi incidències. La nostra aproximació es basa en lògica proposicional, codificant el problema en una fórmula de satisfactibilitat Booleana, i aplicant tècniques de reformulació per a la generació de solucions robustes. També presentem un mecanisme per a incorporar flexibilitat a les solucions robustes, de manera que es pugui establir fàcilment el grau desitjat entre robustesa i optimalitat de les solucions.
Resource allocation problems usually include uncertainties that can produce changes in the data of the problem. These changes may cause difficulties in the applicability of the solutions.
This thesis is focused in the elaboration of techniques that take into account such uncertainties while searching for robust solutions, i.e. solutions that can remain valid even if there are changes in the environment. Particularly, we introduce the concept of robustness based on reparability, where a robust solution is one that can be easily repaired when unexpected events occur. Our approach is based in propositional logic, encoding the problem to a Boolean formula, and applying reformulation techniques in order to generate robust solutions. Additionally, we present a mechanism to incorporate flexibility to the robust solutions, so that one can easily set the desired degree between optimality and robustness.
Tureli, Didem Kivanc. "Resource allocation for multicarrier communications /". Thesis, Connect to this title online; UW restricted, 2005. http://hdl.handle.net/1773/6068.
Testo completoLai, John Kwang. "Truthful and Fair Resource Allocation". Thesis, Harvard University, 2013. http://dissertations.umi.com/gsas.harvard:10928.
Testo completoEngineering and Applied Sciences
Reid, Jane Margaret. "Resource allocation during avian incubation". Thesis, University of Glasgow, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.392460.
Testo completoOwen, Robert Wyn. "Strategies for stochastic resource allocation". Thesis, University of Newcastle Upon Tyne, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.315563.
Testo completoRobinson, Edward Robert. "Resource allocation via competing marketplaces". Thesis, University of Birmingham, 2011. http://etheses.bham.ac.uk//id/eprint/1647/.
Testo completoNguyen, Quang (Quang Duc) 1972. "Optimizing engineering analysis resource allocation". Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/84521.
Testo completoIncludes bibliographical references (p. 72-73).
by Quang Nguyen.
S.M.
M.B.A.
Lien, Yuan-Chuan. "Resource allocation in matching markets /". May be available electronically:, 2007. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.
Testo completoLi, Guoqing. "Resource allocation in OFDMA networks /". Thesis, Connect to this title online; UW restricted, 2004. http://hdl.handle.net/1773/6136.
Testo completoFeldkord, Björn [Verfasser]. "Mobile resource allocation / Björn Feldkord". Paderborn : Universitätsbibliothek, 2020. http://d-nb.info/1204129762/34.
Testo completoMarty, Antoinette T. "Distributive Justice in Resource-Allocation". W&M ScholarWorks, 2002. https://scholarworks.wm.edu/etd/1539626381.
Testo completoRebai, Salma. "Resource allocation in Cloud federation". Thesis, Evry, Institut national des télécommunications, 2017. http://www.theses.fr/2017TELE0006/document.
Testo completoCloud computing is a steadily maturing large-scale model for providing on-demand IT resources on a pay-as-you-go basis. This emerging paradigm has rapidly revolutionized the IT industry and enabled new service delivery trends, including infrastructure externalization to large third-party providers. The Cloud multi-tenancy architecture raises several management challenges for all stakeholders. Despite the increasing attention on this topic, most efforts have been focused on user-centric solutions, and unfortunately much less on the difficulties encountered by Cloud providers in improving their business. In this context, Cloud Federation has been recently suggested as a key solution to the increasing and variable workloads. Providers having complementary resource requirements over time can collaborate and share their respective infrastructures, to dynamically adjust their hosting capacities in response to users' demands. However, joining a federation makes the resource allocation more complex, since providers have to also deal with cooperation decisions and workload distribution within the federation. This is of crucial importance for cloud providers from a profit standpoint and especially challenging in a federation involving multiple providers and distributed resources and applications. This thesis addresses profit optimization through federating and allocating resources amongst multiple infrastructure providers. The work investigates the key challenges and opportunities related to revenue maximization in Cloud federation, and defines efficient strategies to govern providers' cooperation decisions. The goal is to provide algorithms to automate the selection of cost-effective distributed allocation plans that simultaneously satisfy user demand and networking requirements. We seek generic and robust models able to meet the new trends in Cloud services and handle both simple and complex requests, ranging from standalone VMs to composite services requiring the provisioning of distributed and connected resources. In line with the thesis objectives, we first provide a survey of prior work on infrastructure resource provisioning in Cloud environments. The analysis mainly focuses on profit-driven allocation models in Cloud federations and the associated gaps and challenges with emphasis on pricing and networking issues. Then, we present a novel exact integer linear program (ILP), to assist IaaS providers in their cooperation decisions, through optimal "insourcing", "outsourcing" and local allocation operations. The different allocation decisions are treated jointly in a global optimization formulation that splits resource request graphs across federation members while satisfying communication requirements between request subsets. In addition to the request topology, this partitioning takes into account the dynamic prices and quotas proposed by federation members as well as the costs of resources and their networking. The algorithm performance evaluation and the identified benefits confirm the relevance of resource federation in improving providers' profits and shed light into the most favorable conditions to join or build a federation. Finally, a new topology-aware allocation heuristic is proposed to improve convergence times with large-scale problem instances. The proposed approach uses a Gomory-Hu tree based clustering algorithm for request graphs partitioning, and a Best-Fit matching strategy for subgraphs placement and allocation. Combining both techniques captures the essence of the optimization problem and meets the objectives, while speeding up convergence to near-optimal solutions by several orders of magnitude
Rebai, Salma. "Resource allocation in Cloud federation". Electronic Thesis or Diss., Evry, Institut national des télécommunications, 2017. http://www.theses.fr/2017TELE0006.
Testo completoCloud computing is a steadily maturing large-scale model for providing on-demand IT resources on a pay-as-you-go basis. This emerging paradigm has rapidly revolutionized the IT industry and enabled new service delivery trends, including infrastructure externalization to large third-party providers. The Cloud multi-tenancy architecture raises several management challenges for all stakeholders. Despite the increasing attention on this topic, most efforts have been focused on user-centric solutions, and unfortunately much less on the difficulties encountered by Cloud providers in improving their business. In this context, Cloud Federation has been recently suggested as a key solution to the increasing and variable workloads. Providers having complementary resource requirements over time can collaborate and share their respective infrastructures, to dynamically adjust their hosting capacities in response to users' demands. However, joining a federation makes the resource allocation more complex, since providers have to also deal with cooperation decisions and workload distribution within the federation. This is of crucial importance for cloud providers from a profit standpoint and especially challenging in a federation involving multiple providers and distributed resources and applications. This thesis addresses profit optimization through federating and allocating resources amongst multiple infrastructure providers. The work investigates the key challenges and opportunities related to revenue maximization in Cloud federation, and defines efficient strategies to govern providers' cooperation decisions. The goal is to provide algorithms to automate the selection of cost-effective distributed allocation plans that simultaneously satisfy user demand and networking requirements. We seek generic and robust models able to meet the new trends in Cloud services and handle both simple and complex requests, ranging from standalone VMs to composite services requiring the provisioning of distributed and connected resources. In line with the thesis objectives, we first provide a survey of prior work on infrastructure resource provisioning in Cloud environments. The analysis mainly focuses on profit-driven allocation models in Cloud federations and the associated gaps and challenges with emphasis on pricing and networking issues. Then, we present a novel exact integer linear program (ILP), to assist IaaS providers in their cooperation decisions, through optimal "insourcing", "outsourcing" and local allocation operations. The different allocation decisions are treated jointly in a global optimization formulation that splits resource request graphs across federation members while satisfying communication requirements between request subsets. In addition to the request topology, this partitioning takes into account the dynamic prices and quotas proposed by federation members as well as the costs of resources and their networking. The algorithm performance evaluation and the identified benefits confirm the relevance of resource federation in improving providers' profits and shed light into the most favorable conditions to join or build a federation. Finally, a new topology-aware allocation heuristic is proposed to improve convergence times with large-scale problem instances. The proposed approach uses a Gomory-Hu tree based clustering algorithm for request graphs partitioning, and a Best-Fit matching strategy for subgraphs placement and allocation. Combining both techniques captures the essence of the optimization problem and meets the objectives, while speeding up convergence to near-optimal solutions by several orders of magnitude
Mendoza, Charles E. "Resource planning and resource allocation in the construction industry". Thesis, Monterey, California. Naval Postgraduate School, 1995. http://hdl.handle.net/10945/26222.
Testo completoVilajosana, Guillén Xavier. "Distributed Resource Allocation for Contributory Systems". Doctoral thesis, Universitat Oberta de Catalunya, 2009. http://hdl.handle.net/10803/9124.
Testo completoThe 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.
Eriksson, Kristoffer. "Dynamic Resource Allocation in Wireless Networks". Thesis, Linköping University, Communication Systems, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-56776.
Testo completoIn this thesis we investigate different algorithms for dynamic resource allocation in wireless networks. We introduce a general framework for modeling systems whichis applicable to many scenarios. We also analyze a specific scenario with adaptivebeamforming and show how it fits into the proposed framework. We then studytwo different resource allocation problems: Quality-of-Service (QoS) constraineduser scheduling and sum-rate maximization. For user scheduling, we select some“good” set of users that is allowed to use a specific resource. We investigatedifferent algorithms with varying complexities. For the sum-rate maximizationwe find the global optimum through an algorithm that takes advantage of thestructure of the problem by reformulating it as a D.C. program, i.e., a minimizationover a difference of convex functions. We validate this approach by showing that itis more efficient than an exhaustive search at exploring the space of solutions. Thealgorithm provides a good benchmark for more suboptimal algorithms to comparewith. The framework in which we construct the algorithm, apart from being verygeneral, is also very flexible and can be used to implement other low complexitybut suboptimal algorithms.
Farrokh, Arsalan. "Stochastic resource allocation in wireless networks". Thesis, University of British Columbia, 2007. http://hdl.handle.net/2429/31303.
Testo completoApplied Science, Faculty of
Electrical and Computer Engineering, Department of
Graduate
Karlsson, Maria. "Market based programming and resource allocation". Licentiate thesis, Uppsala universitet, Avdelningen för datalogi, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-86157.
Testo completoLessinnes, Mathieu. "Resource allocation for cooperative cognitive radios". Doctoral thesis, Universite Libre de Bruxelles, 2014. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209352.
Testo completoDue to a majority of the abovementioned studies making some constraining assumptions, realistic system designs and experimental demonstrations are much more quiet and unharvested fields. In an effort to help this transition from theory to practice, our second contribution is a four-nodes cognitive network demonstrator, presented in Chapter 3. In particular, we aim at providing a modular platform available for further open collaboration: different options for spectrum sensing, resource allocation, synchronisation and others can be experimented on this demonstrator. As an example, we develop a simple protocol to show that our proposed resource allocation scheme is fully implementable, and that primary users can be avoided using our approach.
Chapter 4 aims at removing another working hypothesis made when developping our resource allocation scheme. Indeed, resource alloca- tion is traditionally a Media Access Control (MAC) layer problem. This means that when solving a resource allocation problem in a network, the routing paths are usually assumed to be known. Conversely, the routing problem, which is a network layer issue, usually assumes that the available capacities on each link of the network (which depend on resource allocation) are known. Nevertheless, these two problems are mathematically entangled, and a cross-layer allocation strategy can best decoupled approaches in several ways, as we discuss in Chapter 4. Accordingly, our third and last contribution is to develop such a cross-layer allocation scheme for the scenario proposed in previous chapters.
All conclusions are summarised in Chapter 5, which also points to a few tracks for future research.
Doctorat en Sciences de l'ingénieur
info:eu-repo/semantics/nonPublished
Moore, Brandon Joseph. "Cooperative strategies for spatial resource allocation". Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1180971769.
Testo completoDahlman, Lena. "Resource aquisition and allocation in lichens". Doctoral thesis, Umeå : Univ, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-115.
Testo completoThanabalasingham, Thayaparan. "Resource allocation in OFDM cellular networks /". Connect to thesis, 2006. http://eprints.unimelb.edu.au/archive/00003227.
Testo completoDemirkol, Mehmet Fatih. "Resource allocation for interfering mimo links". Diss., Georgia Institute of Technology, 2003. http://hdl.handle.net/1853/14799.
Testo completoMenich, Ronald Paul. "Resource allocation in parallel processing systems". Diss., Georgia Institute of Technology, 1991. http://hdl.handle.net/1853/28049.
Testo completoPanigrahi, Saswat. "Resource allocation for multicarrier DSL systems". Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=83879.
Testo completoIn current DSL applications, Crosstalk is kept in control by specifying a fixed peakpower constraint (based on the worst-case) which each user has to obey---a technique known as Static Spectrum Management (SSM). This simplifies the resource allocation to a single-user optimization problem. But the worst-case peak power constraint is overly restrictive and results in poorer rates. Recently Dynamic Spectrum Management (DSM) techniques which dynamically vary the multiuser power allocation for crosstalk control instead of using fixed peak power constraint have proven to provide much better rates. This improvement however comes at the cost of dealing with a more complicated multiuser optimization problem.
On the other hand, due to its unpredictability, external noise (and RFI pickup) has been combated with the use of a suitable safety margin.
Based on application and scenario, Resource Allocation is either performed with the objective of Rate maximization (at a fixed margin) or Margin maximization (at a fixed rate) since each of the quantities indirectly imposes a cap on the other.
But in both rate maximizing and margin maximizing resource allocation algorithms available in literature the bits loaded were always constrained to integers because most scalable modulation schemes such as QAM or PSK support integer bit/symbol. It was initially believed that most (not all) of the granularity losses (due to the integer bit constraint) could be recovered through 'bit-rounding' and 'energy re-scaling'. But this was observed only for the total power constrained case. With the advent of peak power constraint, we show that the room for optimization in the energy domain is severely restricted and granularity losses constitute a significant percentage of the achievable data rate. To recover these losses, we propose the Adaptive Reed Solomon aided Fine Granularity Loading (ARSFGL) scheme---a scheme that jointly optimizes the power, bit and code allocation. For achieving near-continuous rate adaptation, the family of Reed Solomon (RS) codes has been used for their low redundancy, high flexibility in correction capability and highly programmable architecture. Simulation results with realistic VDSL-DMT systems with the currently standardized SSM framework show more than 20% improvement in rate achieved for most cases.
The extension of ARSFGL technique to multiuser (DSM) scenarios results in a purely distributed scheme which provides rates better or equal to the rates achieved by the centralized, optimal (much more complicated) multiuser integer-bit loading scheme.
Further in this work a multiuser margin maximization algorithm is developed. Near-continuous rates provided by the ARSFGL scheme allow continuous bit loading assumption for simplicity. Prior to this work, no multiuser margin maximization algorithm existed, even though the importance of margin maximization is well-recognized. Most existing single-user margin maximization algorithms rely on a fixed crosstalk assumption. But in multiuser (DSM) scenarios each user's power allocation dynamically determines other user's crosstalk. With direct extension of single-user algorithms in multiuser (DSM) scenarios, one user's margin maximization can lead to the failure of other users in meeting their target rates .
We begin by exploring the favorable monotonicity and fairness properties that multi-user margin exhibits over a multiuser rate region and use them to formulate a box-constrained non-linear least squares (NLSQ) problem that can be solved by using a scaled gradient trust region approach with Broyden Jacobian update. This algorithm efficiently converges to a solution providing the best common equal margin to all users while explicitly guaranteeing that each user's target rate requirement is satisfied. The algorithm requires only minimal coordination among users, which makes it suitable for practical implementation.
Farrar, Timothy Martin. "Resource allocation in systems of queues". Thesis, University of Cambridge, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.260462.
Testo completoFerreira, Pena Do Amaral J. A. "Aspects of optimal sequential resource allocation". Thesis, University of Oxford, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.370266.
Testo completoSun, Fanglei, e 孫芳蕾. "Resource allocation in broadband wireless networks". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B40887868.
Testo completoMortimer, David. "RESOURCE ALLOCATION USING TOUCH AND AUDITION". Doctoral diss., University of Central Florida, 2005. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4332.
Testo completoPh.D.
Department of Psychology
Arts and Sciences
Psychology
Dolina, George S. (George Sidrach) 1977. "Intelligent resource allocation in distributed collaboration". Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/80060.
Testo completoIncludes bibliographical references (leaf 39).
by George S. Dolina.
S.B.and M.Eng.
Xu, Yunjian. "Efficiency loss in resource allocation games". Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/77098.
Testo completoCataloged from department-submitted PDF version of thesis. This electronic version was submitted and approved by the author's academic department as part of an electronic thesis pilot project. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (p. 167-176).
The overarching goals of this thesis are to quantify the efficiency loss due to market participant strategic behavior, and to design proper pricing mechanisms that reduce the efficiency loss. The concept of efficiency loss is intimately related to the concept of "price of anarchy," which was advanced by Koutsoupias and Papadimitriou, and compares the maximum social welfare with that achieved at a worst Nash equilibrium. This thesis focuses on the following two topics: (i) For a market with an arbitrary number of participants, how much is the Nash equilibrium close, in the sense of price of anarchy, to a social optimum? (ii) For a resource allocation/pricing mechanism, is the social welfare achieved at an economic equilibrium asymptotically optimal, as the number of market participants goes to infinity? Regarding the first topic, we quantify the efficiency loss in classical Cournot oligopoly games, where multiple oligopolists compete by choosing quantities. We also compare the total profit earned at a Cournot equilibrium to the maximum possible total profit that would be obtained if the suppliers were to collude. For the second topic, related to the efficiency in large economics, we analyze the efficiency of Kelly's proportional allocation mechanism in large-scale wireless communication systems. We study a corresponding Bayesian game in which each user has incomplete information on the state or type of the other users, and show that the social welfare achieved at a Bayes-Nash equilibrium is asymptotically optimal, as the number of users increases to infinity. Finally, for electricity delivery systems, we propose a new dynamic pricing mechanism that explicitly encourages consumers to adapt their consumption so as to offset the variability of demand on conventional units. Through a dynamic game-theoretic formulation, we show that the proposed pricing mechanism achieves social optimality asymptotically, as the number of consumers increases to infinity.
by Yunjian Xu.
Ph.D.
Ku, May. "Resource allocation algorithms in AON network". Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/35956.
Testo completoSuárez, Real Alberto. "Resource allocation for multiuser uplink systems". Nice, 2010. http://www.theses.fr/2010NICE4077.
Testo completoIn this thesis we study the subject of resource allocation for uplink communication systems. When users have target rate constraints and interference cancelation is used at the base station we provide the optimal decoding order and power allocation in order to minimize the power consumption. In addition conditions are derived under which the allocation can be done in a distributed way, with only some knowledge of the statistics of the system. We then proceed to consider multiple-input multiple-output (MIMO) systems, and obtain the optimal precoding matrices such that each user maximizes its own ergodic transmission rate from the sole knowledge of the overall channel statistics. The benefits of using a coordination signal and successive decoding are analyzed. Next, a scenario in which mobile terminals can be simultaneously connected to several base stations, using non-overlapping frequency bands is considered. The optimal power allocation in terms of sum rate is derived for different receiver types and an iterative algorithm proposed to achieve the optimal allocation. Finally, we consider decentralized medium-access control in which many pairwise interactions, where users compete for a medium access opportunity, occur between randomly selected users that belong to a large population. The choice of power level is done by each user, and both team and noncooperative scenarios are analyzed
Zhou, Jihai. "Resource allocation in ad hoc networks". Thesis, Imperial College London, 2011. http://hdl.handle.net/10044/1/6928.
Testo completoSun, Fanglei. "Resource allocation in broadband wireless networks". Click to view the E-thesis via HKUTO, 2008. http://sunzi.lib.hku.hk/hkuto/record/B40887868.
Testo completoDhamdhere, Ashay. "Resource allocation in interference limited systems /". Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2004. http://wwwlib.umi.com/cr/ucsd/fullcit?p3129956.
Testo completoNsoh, Stephen Atambire. "Resource allocation in WiMAX mesh networks". Thesis, Lethbridge, Alta. : University of Lethbridge, Dept. of Mathematics and Computer Science, c2012, 2012. http://hdl.handle.net/10133/3371.
Testo completoix, 77 leaves : ill. ; 29 cm
Gonzalez, Roxana M. "Individual Versus Group Resource-Allocation Performance". W&M ScholarWorks, 2001. https://scholarworks.wm.edu/etd/1539626341.
Testo completoZhang, Peter Yun. "Dynamic and robust network resource allocation". Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/123565.
Testo completoThesis: Ph. D. in Engineering Systems, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2019
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 139-150).
Networks are essential modeling tools in engineering, business, and public policy research. They can represent physical connections, such as manufacturing processes. They can be relationships among people, such as patient treatment in healthcare. They can also represent abstract interactions, such as the biological reaction between a certain vaccine and a certain virus. In this work, we bring several seemingly disparate problems under the same modeling framework, and show their thematic coherence via the angle of dynamic optimization on networks. Our research problems are drawn from business risk management, public health security, and public policy on vaccine selection. A common theme is the integrative design of (1) strategic resource placement on a network, and (2) operational deployment of such resources. We outline the research questions, challenges, and contributions as follows.
Modern automotive manufacturing networks are complex and global, comprising tens of thousands of parts and thousands of plants and suppliers. Such interconnection leaves the network vulnerable to disruptive events. A good risk mitigation decision support system should be data-driven, interpretable, and computational efficient. We devise such a tool via a linear optimization model, and integrate the model into the native information technology system at Ford Motor Company. In public security, policymakers face decisions regarding the placement of medical resources and training of healthcare personnel, to minimize the social and economic impact of potential large scale bio-terrorism attacks. Such decisions have to integrate the strategic positioning of medical inventories, understanding of adversary's behavior, and operational decisions that involve the deployment and dispensing of medicines.
We formulate a dynamic robust optimization model that addresses this decision question, apply a tractable solution heuristic, and prove theoretical guarantees of the heuristic's performance. Our model is calibrated with publicly available data to generate insights on how the policymakers should balance investment between medical inventory and personnel training. The World Health Organization and regional public health authorities decide on the influenza (flu) vaccine type ahead of flu season every year. Vaccine effectiveness has been limited by the long lead time of vaccine production - during the production period, flu viruses may evolve and vaccines may become less effective. New vaccine technologies, with much shorter production lead times, have gone through clinical trials in recent years. We analyze the question of optimal vaccine selection under both fast and slow production technologies. We formulate the problem as a dynamic distributionally robust optimization model.
Exploiting the network structure and using tools from discrete convex analysis, we prove some structural properties, which leads to informative comparative statics and tractable solution methods. With publicly available data, we quantify the societal benefit of current and future vaccine production technologies. We also explore the reduction in disease burden if WHO expand vaccine portfolio to include more than one vaccine strain per virus subtype. In each of the applications, our main contributions are four-fold. First, we develop mathematical models that capture the decision process. Second, we provide computational technology that can efficiently process these models and generate solutions. Third, we develop theoretical tools that guarantee the performance of these computational technology. Last, we calibrate our models with real data to generate quantitative and implementable insights.
by Peter Yun Zhang.
Ph. D. in Engineering Systems
Ph.D.inEngineeringSystems Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society
Petrova, Marina [Verfasser]. "Cognitive resource manager framework for optimal resource allocation / Marina Petrova". Aachen : Hochschulbibliothek der Rheinisch-Westfälischen Technischen Hochschule Aachen, 2011. http://d-nb.info/1014458196/34.
Testo completoBusacca, Fabio Antonino. "AI for Resource Allocation and Resource Allocation for AI: a two-fold paradigm at the network edge". Doctoral thesis, Università degli Studi di Palermo, 2022. https://hdl.handle.net/10447/573371.
Testo completoMohamed, Omer Yusuf Adam. "Resource Allocation for Improved Performance and Resource Efficiency in Cloud Computing". Thesis, The University of Sydney, 2017. http://hdl.handle.net/2123/17596.
Testo completoUrlichs, Robert. "Patterns of resource allocation decisions in organisations /". Wiesbaden : Deutscher Universitäts-Verlag, 2006. http://opac.nebis.ch/cgi-bin/showAbstract.pl?u20=3835002090.
Testo completoCaceres-Delpiano, Julio F. "Testing economic models of household resource allocation". College Park, Md. : University of Maryland, 2005. http://hdl.handle.net/1903/2905.
Testo completoThesis 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.
Harell, Dustin Ashley. "Resource conservation and allocation via process integration". Diss., Texas A&M University, 2004. http://hdl.handle.net/1969.1/485.
Testo completoLi, Cai. "Simulator for Resource Allocation in Hybrid Networks". Thesis, Linköping University, Department of Computer and Information Science, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2808.
Testo completoMuch work has been done in simulating traditional cellular networks. But with the incoming of ad-hoc network technology, the next generation networks will employ hybrid network architectures using both cellular and ad-hoc networking concepts.
We investigate how to create a simulator being able to simulate a hybrid wireless network. This involves setting up a cellular network and an ad-hoc network respectively. However, the most important thing is how to integrate them seamlessly.
Fortunately, there has already been a simulator called SIMRA which simulates a UMTS cellular network. Therefore, this thesis work is greatly simplified as how to extend and improve SIMRA to implement a simulator for hybrid wireless network. We selected J-sim as the developing platform for our simulator and our development was greatly based on the wireless package provided by the latest version of J-sim.
To evaluate the new simulator, different resource allocation algorithms were run against it and the results were compared to those generated by earlier extensions to SIMRA under the same simulation settings. It showed that the resource allocation algorithms behaved similarly under the hybrid wireless network environment. Nevertheless, there are some discrepancies in behaviors of algorithms used for evaluation that still need to be studied.
Lindblom, Johannes. "Resource Allocation on the MISO Interference Channel". Licentiate thesis, Linköping University, Linköping University, Communication Systems, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-55102.
Testo completoThe need for wireless communications has increased during the last decades. To increase the data rates of the communication links there is a need of allocating larger frequency bands. These bands are strictly regulated and the majority of the frequencies are allocated to licensed systems. The splitting of the bandwidth is orthogonal, which mean that the different systems are not interfering each other. But, orthogonal splitting is inefficient since it does not exploit all degrees of freedom in the wireless channels.
There are also unlicensed bands where different systems co-exist and operate simultaneously in a non-orthogonal manner and interfere each other. This interference degrades the performance of each system. This motivates the use of so-called spectrum sharing techniques for interference management.
The spectrum sharing can be modeled via the so-called interference channel (IFC). This consists of at least two transmitter (TX)-receiver (RX) pairs. These pairs can share resources such as frequency, time, power, code, or space. Here, the focus is on the sharing of spatial resources. By employing multiple antennas at the TXs, spatial diversity is obtained and it is possible to steer the power in any spatial direction. Assuming a single antenna at each RX we get the so-called multiple-input single-output (MISO) IFC.
There is a conflict inherent in the IFC since the TX-RX pairs optimize conflicting objectives, e.g., the data rates. To analyze this conflict we use game-theoretic concepts. In general, the situation where the TXs transmit in the directions which are optimal for their objective is inefficient. That is, it is possible increase all rates of some (or all) TX-RX pairs without decreasing the rate of any of the pairs. To do so, the TXs change their strategies such that interference is decreased.
We define several rate regions, which depend on the channel model and channelstate information at the transmitters. Also, some of the most important game-theoretic operating points are described.
An, Na. "Resource Modeling and Allocation in Competitive Systems". Diss., Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/6997.
Testo completo