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Vijayakumar, Smita. "A Framework for Providing Automatic Resource and Accuracy Management in a Cloud Environment." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1274194090.
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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.
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In this thesis we investigate different algorithms for dynamic resource allocation in wireless networks. We introduce a general framework for modeling systems whichis applicable to many scenarios. We also analyze a specific scenario with adaptivebeamforming and show how it fits into the proposed framework. We then studytwo different resource allocation problems: Quality-of-Service (QoS) constraineduser scheduling and sum-rate maximization. For user scheduling, we select some“good” set of users that is allowed to use a specific resource. We investigatedifferent algorithms with varying complexities. For the sum-rate maximizationwe find the global optimum through an algorithm that takes advantage of thestructure of the problem by reformulating it as a D.C. program, i.e., a minimizationover a difference of convex functions. We validate this approach by showing that itis more efficient than an exhaustive search at exploring the space of solutions. Thealgorithm provides a good benchmark for more suboptimal algorithms to comparewith. The framework in which we construct the algorithm, apart from being verygeneral, is also very flexible and can be used to implement other low complexitybut suboptimal algorithms.
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Zhang, Peter Yun. "Dynamic and robust network resource allocation." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/123565.
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This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Thesis: 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
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Hashmi, Ziaul Hasan. "Dynamic resource allocation for cognitive radio systems." Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/961.
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Cognitive Radio (CR) is considered to be a novel approach to improve the underutilization of precious radio resources by exploiting the unused licensed spectrum in dynamically changing environments. Designing efficient resource allocation algorithms for dynamic spectrum sharing and for power allocation in OFDM-CR networks is still a challenging problem. In this thesis, we specifically deal with these two problems.
Dynamic spectrum sharing for the unlicensed secondary users (SU)s with device coordination could minimize the wastage of the spectrum. But this is a feasible approach only if the network considers the fairness criterion. We study the dynamic spectrum sharing problem for device coordinated cognitive radio networks with respect to fairness. We propose a simple modified proportional fair algorithm for a dynamic spectrum sharing scenario with two constraints, time and utility. Utility is measured by the amount of data processed and time is measured as the duration of a slot. This algorithm could result in variable or fixed length time slots. We will discuss the several controls possible on the algorithm and the possible extension of this algorithm for multicarrier OFDM based CR systems.
Traditional water-filling algorithm is inefficient for OFDM-CR networks due to the interaction with primary users (PU)s. We consider reliability/availability of subcarriers or primary user activity for power allocation. We model this aspect mathematically with a risk-return model by defining a general rate loss function. We then propose optimal and suboptimal algorithms to allocate power under a fixed power budget for such a system with linear rate loss. These algorithms as we will see allocate more power to more reliable subcarriers in a water-filling fashion with different water levels. We compare the performance of these algorithms for our model with respect to water-filling solutions. Simulations show that suboptimal schemes perform closer to optimal scheme although they could be implemented with same complexity as water-filling algorithm. We discuss the linearity of loss function and guidelines to choose its coefficients by obtaining upper bounds on them. Finally we extend this model for interference-limited OFDM-CR systems.
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Su, Guan-Ming. "Dynamic resource allocation for multiuser video streaming." College Park, Md. : University of Maryland, 2006. http://hdl.handle.net/1903/3982.
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Thesis (Ph. D.) -- University of Maryland, College Park, 2006.Thesis research directed by: Electrical Engineering. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Usaha, Wipawee. "Resource allocation in networks with dynamic topology." Thesis, Imperial College London, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.405658.
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Tuli, Gaurav 1978. "Dynamic QoS resource allocation in Bluetooth piconet." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/86754.
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Ferreira, 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.
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Västfält, Anders, and Matthias Erll. "A Dynamic Resource Allocation Framework for IT Consultancies." Thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Informatik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-15710.
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This Master thesis provides a framework for analysis of the resource planning and allocation processes within an IT consultant firm. The aim is, to identify information, which can be reflected in an information system. The framework has been developed using multi-grounded theory method, considering theories from the areas of information systems design, project business performance, enterprise planning, and project planning. Based on a main process view and hypothesized information requirements, the dynamic processes of sales, project resource planning, miscellaneous activity planning, project portfolio planning, resource allocation and general management are discussed, along with their underlying concepts. A case study has been conducted, to test the validity of the framework and to evaluate its applicability. The findings are compared and contrasted to our frame of reference during analysis. From a reflection on the analysis, changes are proposed to the firm under study, as well as our framework.
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Ivan-Roşu, Daniela. "Dynamic resource allocation for adaptive real-time applications." Diss., Georgia Institute of Technology, 1999. http://hdl.handle.net/1853/9200.
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Al, Ghamdi Mohammed A. "Predictive dynamic resource allocation for web hosting environments." Thesis, University of Warwick, 2012. http://wrap.warwick.ac.uk/51600/.
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E-Business applications are subject to significant variations in workload and this can cause exceptionally long response times for users, the timing out of client requests and/or the dropping of connections. One solution is to host these applications in virtualised server pools, and to dynamically reassign compute servers between pools to meet the demands on the hosted applications. Switching servers between pools is not without cost, and this must therefore be weighed against possible system gain. This work is concerned with dynamic resource allocation for multi-tiered, clusterbased web hosting environments. Dynamic resource allocation is reactive, that is, when overloading occurs in one resource pool, servers are moved from another (quieter) pool to meet this demand. Switching servers comes with some overhead, so it is important to weigh up the costs of the switch against possible system gains. In this thesis we combine the reactive behaviour of two server switching policies – the Proportional Switching Policy (PSP) and the Bottleneck Aware Switching Policy (BSP) – with the proactive properties of several workload forecasting models. We evaluate the behaviour of the two switching policies and compare them against static resource allocation under a range of reallocation intervals (the time it takes to switch a server from one resource pool to another) and observe that larger reallocation intervals have a negative impact on revenue. We also construct model- and simulation-based environments in which the combination of workload prediction and dynamic server switching can be explored. Several different (but common) predictors – Last Observation (LO), Simple Average (SA), Sample Moving Average (SMA) and Exponential Moving Average (EMA), Low Pass Filter (LPF), and an AutoRegressive Integrated Moving Average (ARIMA) – have been applied alongside the switching policies. As each of the forecasting schemes has its own bias, we also develop a number of meta-forecasting algorithms – the Active Window Model (AWM), the Voting Model (VM), the Selective Model (SM), the Dynamic Active Window Model (DAWM), and a method based on Workload Pattern Analysis (WPA). The schemes are tested with real-world workload traces from several sources to ensure consistent and improved results. We also investigate the effectiveness of these schemes on workloads containing extreme events (e.g. flash crowds). The results show that workload forecasting can be very effective when applied alongside dynamic resource allocation strategies.
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Chester, Adam P. "Towards effective dynamic resource allocation for enterprise applications." Thesis, University of Warwick, 2011. http://wrap.warwick.ac.uk/49959/.
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The growing use of online services requires substantial supporting infrastructure. The efficient deployment of applications relies on the cost effectiveness of commercial hosting providers who deliver an agreed quality of service as governed by a service level agreement for a fee. The priorities of the commercial hosting provider are to maximise revenue, by delivering agreed service levels, and minimise costs, through high resource utilisation. In order to deliver high service levels and resource utilisation, it may be necessary to reorganise resources during periods of high demand. This reorganisation process may be manual or alternatively controlled by an autonomous process governed by a dynamic resource allocation algorithm. Dynamic resource allocation has been shown to improve service levels and utilisation and hence, profitability. In this thesis several facets of dynamic resource allocation are examined to asses its suitability for the modern data centre. Firstly, three theoretically derived policies are implemented as a middleware for a modern multi-tier Web application and their performance is examined under a range of workloads in a real world test bed. The scalability of state-of-the art resource allocation policies are explored in two dimensions, namely the number of applications and the quantity of servers under control of the resources allocation policy. The results demonstrate that current policies presented in the literature demonstrate poor scalability in one or both of these dimensions. A new policy is proposed which has significantly improved scalability characteristics and the new policy is demonstrated at scale through simulation. The placement of applications in across a datacenter makes them susceptible to failures in shared infrastructure. To address this issue an application placement mechanism is developed to augment any dynamic resource allocation policy. The results of this placement mechanism demonstrate a significant improvement in the worst case when compared to a random allocation mechanism. A model for the reallocation of resources in a dynamic resource allocation system is also devised. The model demonstrates that the assumption of a constant resource reallocation cost is invalid under both physical reallocation and migration of virtualised resources.
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Hosein, Patrick Ahamad. "A class of dynamic nonlinear resource allocation problems." Thesis, Massachusetts Institute of Technology, 1989. http://hdl.handle.net/1721.1/14258.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1990.Includes bibliographical references (leaves 213-214).
by Patrick Ahamad Hosein.
Ph.D.
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Ng, Peng-Teng Peter. "Distributed dynamic resource allocation in multi-model situations." Thesis, Massachusetts Institute of Technology, 1985. http://hdl.handle.net/1721.1/15184.
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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.
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Wu, Cynara C. "Dynamic resource allocation in CDMA cellular communications systems." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/9332.
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Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.Includes bibliographical references (p. 115-117).
Efficient resource utilization is the primary problem in cellular communication systems. In this thesis, we combine the main resource issues for CDMA systems, admission control and power control, in a single framework. The framework uses a formulation that is general enough to incorporate all significant parameters of a system, yet tractable to compute. We formulate the resource allocation problem as a Markov decision process. Due to the enormous size of the state space, applying the traditional solution technique, dynamic programming, is impractical. We therefore consider approximation techniques. As a first step towards simplification, we divide the problem into two subproblems: optimal admission control with heuristic power control and optimal power control with heuristic admission control. We formulate the problem of optimal admission control as a Markov decision process and consider several approximate dynamic programming techniques. We apply these techniques to a simulated system and obtain results that improve significantly upon two commonly used policies, the greedy policy and the reservation policy. We then consider the minimization of the total power transmitted over given discrete sets of available power levels subject to maintaining an acceptable signal quality for each mobile. We develop sequential and distributed iterative algorithms for solving a more general version of this integer programming problem and show that they find the optimal solution in a finite number of iterations which is polynomial in the number of power levels and the number of mobiles.
by Cynara C. Wu.
Ph.D.
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Yilmaz, Tuba. "Dynamic resource allocation in manufacturing and service industries." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/51729.
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In this thesis, we study three applications of dynamic resource allocation: the first two consider dynamic lead-time quotation in make-to-order (MTO) systems with substitutable products and order cancellations, respectively; and the third application is a manpower allocation problem with job-teaming constraints. Matching supply and demand for manufacturing and service industries has been a fundamental focus of operations management literature, which concentrated on optimizing or improving supply-side decisions since demand has generally been assumed to be exogenously determined. However, recent business trends and advances in consumer behavior modeling have shown that demand for goods and services can clearly be shaped by various decisions that a firm makes, such as price and lead-time. In fact, competition between companies is no longer mainly based on price or product features; lead-time is one of the strategic measures to evaluate suppliers. In MTO manufacturing or service environments that aim to satisfy the customers' unique needs, lead-time quotation impacts the actual demand of the products and the overall profitability of the firm. In the first two parts of the thesis, we study the dynamic lead-time quotation problem in pure MTO (or service) systems characterized by lead-time sensitive Poisson demand and exponentially distributed service times. We formulate the problem as an infinite horizon Markov decision process (MDP) with the objective of maximizing the long-run expected average profit per unit time, where profits are defined to specifically account for delays in delivery of the customer orders. We study dynamic lead-time quotation problem in two particular settings; one setting with the possibility of demand substitution and another setting with order cancellations. The fundamental trade-off in lead-time quotation is between quoting short lead-times and attaining them. In case of demand substitution, i.e., in presence of substitutable products and multiple customer classes with different requirements and margins, this trade-off also includes capacity allocation and order acceptance decisions. In particular, one needs to decide whether to allocate capacity to a low-margin order now, or whether to reserve capacity for potential future arrivals of high-margin orders by considering customer preferences, the current workload in the system, and the future arrivals. In the case of order cancellations, one needs to take into account the probability of cancellation of orders currently in the system and quote lead-times accordingly; otherwise quotation of a longer lead-time may result in the loss of customer order, lower utilization of resources, and, in turn, reduced in profits. In Chapter 2, we study a dynamic lead-time quotation problem in a MTO system with two (partially) substitutable products and two classes of customers. Customers decide to place an order on one of the products or not to place an order, based on the quoted lead-times. We analyze the optimal profit and the structure of the optimal lead-time policy. We also compare the lead-time quotes and profits for different quotation strategies (static vs. dynamic) with or without substitution. Numerical results show that substitution and dynamic quotation have synergetic effects, and higher benefits can be obtained by dynamic quotation and/or substitution when difference in product revenues or arrival rates, or total traffic intensity are higher. In Chapter 3, we study a dynamic lead-time quotation problem in a MTO system with single product considering the order cancellations. The order cancellations can take place during the period that the order is being processed (either waiting or undergoing processing), or after the processing is completed, at the delivery to the customer. We analyze the behavior of optimal profit in terms of cancellation parameters. We show that the optimal profit does not necessarily decrease as cancellation rate increases through a numerical study. When the profit from a cancelled order, arrival rate of customers, or lead-time sensitivity of customers are high, there is a higher probability that optimal profit increases as cancellation rate increases. We also compare the cancellation scenarios with the corresponding no-cancellation scenarios, and show that there exists a cancellation scenario that is at least as good in terms of profit than a no-cancellation scenario for most of the parameter settings. In Chapter 4, we study the Manpower Allocation Problem with Job-Teaming Constraints with the objective of minimizing the total completion time of all tasks. The problem arises in various contexts where tasks require cooperation between workers: a team of individuals with varied expertise required in different locations in a business environment, surgeries requiring different composition of doctors and nurses in a hospital, a combination of technicians with individual skills needed in a service company. A set of tasks at random locations require a set of capabilities to be accomplished, and workers have unique capabilities that are required by several tasks. Tasks require synchronization of workers to be accomplished, hence workers arriving early at a task have to wait for other required workers to arrive in order to start processing. We present a mixed integer programming formulation, strengthen it by adding cuts and propose heuristic approaches. Experimental results are reported for low and high coordination levels, i.e., number of workers that are required to work simultaneously on a given task.
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Bansal, Gaurav. "Dynamic resource allocation for OFDM-based cognitive radio systems." Thesis, University of British Columbia, 2011. http://hdl.handle.net/2429/33275.
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Cognitive radio (CR) is an emerging technology that would improve spectrum utilization by exploiting unused spectrum in dynamically changing environments. We investigate the design of link adaptation algorithms (e.g., adaptive power and bit loading) for orthogonal frequency division multiplexing (OFDM)-based CR systems. Different power and bit loading schemes can be designed for CR users which exploits the time varying nature of fading gains across the OFDM subcarriers. However, one of the challenges here is to ensure that the interference caused to the primary users (PUs) remains below the target interference threshold. Therefore, not only do we need to consider the fading gains, but also the spectral distance of the subcarriers from the PU's band. In this thesis, we propose an optimal power loading algorithm, assuming that the rate can be varied continuously, for an OFDM-based CR system. The downlink transmission capacity of the CR user is thereby maximized, while the interference introduced to the PU remains within a tolerable range. We investigate the case of discrete (or integer) rate adaptation. A sub-optimal scheme for integer bit loading is presented which approximates the optimal continuous rate value to a nearest integer. Next, we propose schemes that maximize the capacity of CR users when only imperfect channel state information (CSI) is available at the CR transmitter while guaranteeing the statistical interference constraint. Further, we propose resource allocation schemes for a multiuser scenario where power is loaded for CR users not only in the subcarriers where PU is not present (overlay fashion) but also in the subcarriers where PU is present (underlay fashion). Finally, for the scenarios where the link between CR source and destination might be weak and not reliable for communication, we employ relays and propose relay and power allocation schemes. Numerical results have been presented for all the proposed algorithms.
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Slegers, Joris. "On dynamic resource allocation in systems with bursty sources." Thesis, Newcastle upon Tyne : University of Newcastle upon Tyne, 2009. http://hdl.handle.net/10443/159.
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Secor, Matthew J. (Matthew Joelson). "Geometric modeling and analysis of dynamic resource allocation mechanisms." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/8769.
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Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2001.Includes bibliographical references (p. 159-163).
The major contribution of this thesis is the investigation of a specific resource allocation optimization problem whose solution has both practical application as well as theoretical interest. It is presented as a specific case of a more general modeling framework we put forth. The underlying question asks how to partition a given resource into a fixed number of parts such that the elements of the resulting partition can be scheduled among a set of user requests to minimize the worst case difference between the schedule and the requests. This particular allocation problem has not been studied before. The general problem is difficult in part because the evaluation of the objective problem is a difficult task by itself. We present a novel algorithm for its exact solution in a constrained setting and discussion of the unconstrained setting in, followed by a number of practical applications of these solutions. The solution to the constrained optimization problem is shown to provide sizable benefits in allocation efficiency in a number of contexts at a minimal implementation cost. The specific contexts we look at include communication over a shared channel, allocation of many small channels to a few users and package delivery from a central office to a number of satellite offices. We also present a set of new fairness results for auction-based allocation mechanisms and show how these mechanisms also fall within our modeling framework. Specifically, we look at using auctions as mechanisms to allocate an indivisible shared resource fairly among a number of users. We establish that a straightforward approach as has been tried in the literature does not guarantee an fair allocation over a long time scale and provide a modified approach that does guarantee a fair allocation. We also show that by allowing users to strategize when bidding on the resource we can avoid the problem of unfairness, for some simple cases. This analysis has not been seen in existing literature. Finally, an analysis of the deterministic and stochastic stability of our class of models is presented that applies to a large subset of the models within our framework. The deterministic stability results presented establish the ultimate boundedness of the lag of deterministically stabilizable models in our framework under a wide variety of quantizer-based scheduling rules. This variety of available rules can be used to further control the behavior of the lag of a stable mechanism. We also discuss the application of existing stochastic stability theory to a large subset of the stochastic models in our framework. This is a straightforward usage of existing stability results based on verifying the satisfaction of a stochastic drift condition.
by Matthew Secor.
Ph.D.
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Rincon, Mateus Cesar Augusto. "Dynamic resource allocation for energy management in data centers." [College Station, Tex. : Texas A&M University, 2008. http://hdl.handle.net/1969.1/ETD-TAMU-3182.
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Lessinnes, 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.
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Resource allocation consists in allocating spectrum and power on every link of a network, possibly under power and rate requirements. In the context of cognitive radios, almost 15 years of research produced an impressive amount of theoretical contributions, exploring a wide range of possibilities. However, despite the ever-growing list of imaginable scenarios, we observe in Chapter 2 that most of these studies are based on similar working hypotheses. Our first contribution is to challenge some of these hypotheses, and propose a novel resource allocation scheme. Sticking to realistic assumptions, we show how our scheme reduces both computational complexity and control traffic, compared to other state-of-the-art techniques.Due 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
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Shi, Ning. "Dynamic resource allocation problems with uncertainties and complex work rules." View abstract or full-text, 2007. http://library.ust.hk/cgi/db/thesis.pl?IELM%202007%20SHI.
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Donyina, Adwoa Dansoa. "Stochastic modelling & analysis of dynamic human-resource allocation (StADy)." Thesis, University of Leicester, 2011. http://hdl.handle.net/2381/9915.
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Business processes require involvement of technical components as well as humans to achieve their objectives. However, humans are only predictable to a degree of certainty because, while guided by policies and regulations, they retain the freedom to ignore established procedures or positively react to unforeseen events. Since we cannot change people, we have to be able to recognize their unpredictable behaviour by organising processes in such a way as to benefit from the flexibility of their actions and deal with the problems that arise from it. Business processes tend to be a structured sequence of events; however the assignment of humans to scheduled cases is unstructured. Hence, it is difficult to accurately model and simulate the flexibility of human resource allocation without considering the impact of unpredictable human behaviour. While business processes often have a rigid structure, determining sequences of actions on each individual case, there is flexibility in the selection of cases to be processed as well as in the assignment of human resources. However, such a flexible use of resources poses its own challenges, making process execution difficult to model and predict. In this thesis I propose a methodology and language to support the modelling and evaluation of business process executions with flexible assignment of human resources. The main idea is to model configurations of a business process as graphs and use graph transformation rules in a UML-like syntax to describe the process execution. This model allows to define conditions to temporarily permit actors to exceed their roles in exceptional (escalated) situations, without causing legal repercussions. The evaluation of process execution models is supported by the use of stochastic graph transformations, which allow the qualitative analysis of different organizational policies through simulation. The methodology is presented in four stages of (1) business modelling, (2) process execution design, (3) process encoding and (4) performance evaluation. A case study of a pharmacy process is used to evaluate the approach.
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Beghelli, Alejandra Liliana Zapata. "Resource allocation and scalability in dynamic wavelength-routed optical networks." Thesis, University College London (University of London), 2006. http://discovery.ucl.ac.uk/1445164/.
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This thesis investigates the potential benefits of dynamic operation of wavelength-routed optical networks (WRONs) compared to the static approach. It is widely believed that dynamic operation of WRONs would overcome the inefficiencies of the static allocation in improving resource use. By rapidly allocating resources only when and where required, dynamic networks could potentially provide the same service that static networks but at decreased cost, very attractive to network operators. This hypothesis, however, has not been verified. It is therefore the focus of this thesis to investigate whether dynamic operation of WRONs can save significant number of wavelengths compared to the static approach whilst maintaining acceptable levels of delay and scalability. Firstly, the wavelength-routed optical-burst-switching (WR-OBS) network architecture is selected as the dynamic architecture to be studied, due to its feasibility of implementation and its improved network performance. Then, the wavelength requirements of dynamic WR-OBS are evaluated by means of novel analysis and simulation and compared to that of static networks for uniform and non-uniform traffic demand. It is shown that dynamic WR-OBS saves wavelengths with respect to the static approach only at low loads and especially for sparsely connected networks and that wavelength conversion is a key capability to significantly increase the benefits of dynamic operation. The mean delay introduced by dynamic operation of WR-OBS is then assessed. The results show that the extra delay is not significant as to violate end-to-end limits of time-sensitive applications. Finally, the limiting scalability of WR-OBS as a function of the lightpath allocation algorithm computational complexity is studied. The trade-off between the request processing time and blocking probability is investigated and a new low-blocking and scalable lightpath allocation algorithm which improves the mentioned trade-off is proposed. The presented algorithms and results can be used in the analysis and design of dynamic WRONs.
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Garrett, Richard A. "Dynamic modeling of arctic resource allocation for oil spill response." Thesis, Rensselaer Polytechnic Institute, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10159829.
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A mixed-integer linear program is proposed to model the dynamic network expansion problem of improving oil spill response capabilities to support energy exploration in the Arctic. Oil spill response operations in this region can be hampered by a lack of existing infrastructure, limited pre-positioned response equipment, and the possibility that response equipment might not arrive in time to mitigate the impact of a spill because of distance and infrastructure limitations. These considerations are modeled by two inter-related constraint sets with the objective of minimized total weighted response time for a set of potential oil spill incidents. One constraint set determines how to dynamically allocate response equipment and improve the infrastructures necessary to stockpile them within a network of response sites. The other set determines how to utilize this stockpile to respond to each task necessary for an incident by scheduling the equipment to complete tasks. These task completion times are subject to deadlines which, if not met, can, instead, require costlier follow-on tasks to be scheduled. The model, its assumptions, and data requirements were assessed by subject matter experts in the United States (U.S.) Coast Guard and a major Oil Spill Response Organization in the context of oil spill response logistics to support energy exploration initiatives in the U.S. Arctic.
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Al-Wasity, A. J. L. "Virtualized dynamic resource allocation algorithm for the internet DiffServ domains." Thesis, University of Salford, 2017. http://usir.salford.ac.uk/43695/.
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The Differentiated Services (DiffServ) architecture has been proposed for providing different levels of service to the Internet Protocol (IP) traffic. Current discussions in the DiffServ networks are focused on managing resources dynamically according to the traffic conditions of the DiffServ router (Per Hop Behaviour). Software Defined Networks (SDN) and Network Function Virtualisation (NFV) technologies have recently emerged in the research agenda to support researchers in managing network domains and to achieve better use of domain resources. This thesis introduces a new scheduling algorithm called “Dynamic Resource Allocation Management - Network Function Virtualization (DRAM-NFV)” to allocate the service classes resources in the proportional delay DiffServ domains. DRAM-NFV algorithm manages the resources among service classes within the edge routers of the DiffServ domains dynamically according to their traffic conditions and manages these resources between the DiffServ domains in the event of congestion based on their traffic conditions at the egress routers of the upstream domain and ingress routers of the downstream domain. The NFV executes the DRAM-NFV algorithm on a virtualized - Network as a Service (NaaS) - cloud infrastructure to manage the SDN controllers for the edge routers of the DiffServ domains through monitoring the traffic conditions in the service classes at the edge routers and reallocating the out-link resources of the edge routers among service classes. A number of test scenarios were conducted in this research in order to test the performance of the DRAM-NFV algorithm. The performance of DRAM-NFV algorithm is compared with the performance of the DWFQ algorithm by comparing the average End to End Delay for service classes traffic and links utilization. The DWFQ algorithm cannot manage resources between DiffServ domains but can manage the resources locally and dynamically for each DiffServ domain separately. The network simulator NS3 has been used to implement these test scenarios and to test the performance of the DRAM-NFV algorithm. The results show that with the DRAM-NFV algorithm, better balance for DiffServ domains resources can be achieved through monitoring the bandwidth hungry service class at the downstream domain and managing its resources at the upstream domains. As a consequence of this, the utilizations of some service classes traffic are improved and the average End to End Delay for overall traffic are also reduced. An example of the improvement that was achieved by managing resources between (upstream and downstream) DiffServ domains dynamically, in test scenario 3- Case Study 2, the average utilization for the highest priority class (SC1) for whole period of simulation at the destination end is increased by 0.175% and the average End to End Delay for overall traffic is also reduced by 800 msec. As a result of reducing the average End to End Delay for overall traffic and improving the utilizations of service classes traffic, the QoS of applications traffic can be improved during the congestion periods in DiffServ domains.
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Zhang, C. "Dynamic topology estimation and resource allocation for power line communication." Thesis, University of Liverpool, 2016. http://livrepository.liverpool.ac.uk/3001025/.
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Power line communication (PLC), which uses existing infrastructure of power delivery for data transfer, is regarded as an economical, pervasive and extensive communication solution for smart grid and home broadband applications. One of the challenges of applying communication technologies to power line network lies in acquirement of channel state information (CSI), which is dependent on network topology. Moreover, the knowledge of topology provides a basis for the design of routing protocols and power flow optimization. Therefore, efficient approaches for dynamic topology estimation are highly demanded. While dynamic routing and resource allocation enable high-speed and multi-tasking communication services over power lines. In this thesis, a dynamic topology estimation scheme for PLC is investigated, and a cross-layer routing and resource allocation scheme assisted by dynamic topology estimation is developed to improve the system performance. In the first contribution, a high-resolution and low-complexity dynamic topology estimation scheme for time-varying indoor PLC networks is proposed. The scheme consists of three parts: a) a time-frequency domain reflectometry (TFDR) based path length estimation method, which requires measurement at a single PLC modem and achieves a much higher resolution than the frequency domain reflectometry (FDR) based method; b) a node-by-node greedy algorithm for topology reconstruction, which is much more computationally efficient than the existing peak-by-peak searching algorithm; c) an impulsive noise assisted dynamic topology re-estimation method, which results in a significant complexity reduction over fixed-frequency re-estimation. In the second contribution, a cross-layer routing and resource allocation (RA) scheme assisted by dynamic topology estimation is proposed to optimize the system throughput of indoor PLC network with heterogeneous delay requirements. The proposed scheme provides a multi-layer solution, which conducts the network layer routing based on the result of PHY layer resource allocation which is constrained by the MAC layer queuing delay. With the dynamic topology estimation proposed in the first contribution, the routing can be solved centrally at the source, which is more robust against topology changes compared to distributed solutions. The proposed cross-layer RA scheme consists of subcarrier allocation (SA) to multiple users and power allocation (PA) to subcarriers satisfying heterogeneous delay requirements. It is demonstrated that the proposed centralized routing strategy achieves a much lower packet loss rate (PLR) than a distributed routing scheme; while with optimal RA, the system throughput is significantly improved compared to the routing schemes without considering RA.
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Jmila, Houda. "Dynamic resource allocation and management in virtual networks and Clouds." Thesis, Evry, Institut national des télécommunications, 2015. http://www.theses.fr/2015TELE0023/document.
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L’informatique en nuage (Cloud computing) est une technologie prometteuse facilitant la réservation et de l'utilisation des ressources d’une manière flexible et dynamique. En plus des ressources informatiques traditionnelles, les utilisateurs du Cloud attendent à ce que des ressources réseaux leurs soient dédiées afin de faciliter le déploiement des fonctions et services réseau. Ils souhaitent pouvoir gérer l'ensemble d'un réseau virtuel (VN) ou infrastructure. Ainsi, les fournisseurs du Cloud doivent déployer des solutions de provisionnement des ressources dynamiques et adaptatives afin d’allouer des réseaux virtuels qui reflètent les besoins variables dans le temps des applications hébergés dans le Cloud. L’état de l’art sur l’allocation des réseaux virtuels s’est uniquement intéressé au problème de mapping des nœuds et liens virtuels composant une demande de réseau virtuel dans les nœuds et chemins du réseau de physique (infrastructure Cloud), connu sous le nom du problème de virtual network embedding (VNE). Peu d'attention a été accordée à la gestion des ressources allouées pour répondre en permanence aux besoins variables des réseaux virtuels hébergés dans le réseau physique et afin d'assurer une utilisation efficace des ressources. L'objectif de cette thèse est de permettre l'allocation des réseaux virtuels d’une manière dynamique et préventive pour faire face aux fluctuations de la demande au cours de la durée de vie du réseau virtuel, et pour améliorer l'utilisation des ressources du substrat. Pour atteindre ces objectifs, la thèse propose d'adaptation des algorithmes d'allocation des ressources pour répondre à l’évolution des demandes du réseau virtuel. Premièrement, nous allons étudier en profondeur l'extension d'un nœud virtuel, à savoir le cas où un nœud virtuel hébergé nécessite plus de ressources alors le nœud physique qui l’héberge n'a pas assez de ressources disponibles. Deuxièmement, nous allons améliorer la proposition précédente afin de considérer la rentabilité du réseau de substrat. Et enfin, nous allons gérer la variation de la demande en bande passante dans les liens virtuels. Par conséquent, la première partie de cette thèse fournit un algorithme heuristique qui traite la fluctuation de la demande dans les nœuds virtuels. L'idée principale de l'algorithme est de réallouer un ou plusieurs nœuds virtuels co-localisés dans du nœud de substrat, qui héberge le nœud en évolution pour libérer des ressources (ou faire de la place) pour le nœud en évolution. En plus de réduire le coût de réaffectation, notre proposition prend en compte et réduit l'interruption de service pendant la migration. L'algorithme précédent a été étendu pour concevoir un algorithme de reconfiguration préventif pour améliorer la rentabilité du réseau physique. En fait, notre proposition profite de la perturbation de la demande de ressources pour ranger le réseau physique à un coût minimal et sans perturbations. Lors de la réaffectation des nœuds virtuels pour faire place pour le nœud en extension, nous réaffectant les liens virtuels les plus congestionnées dans des ressources physiques moins saturées afin d’équilibrer la charge sur le réseau. Notre proposition offre le meilleur compromis entre le coût de réaffectation et l'équilibrage des charges. Enfin, un framework distribué, parallèle et à vue locale a été mis au point pour traiter toutes les formes de fluctuations de la demande en bande passante dans les liens virtuels. Elle se compose d'un contrôleur et trois algorithmes exécutés dans chaque nœud du substrat d'une manière distribuée et parallèle. Le framework est basé sur l'auto-stabilisation, et peut gérer de nombreuses et différentes formes de variations de la demande de bande passante simultanémentCloud computing is a promising technology enabling IT resources reservation and utilization on a pay-as-you-go manner. In addition to the traditional computing resources, cloud tenants expect compete networking of their dedicated resources to easily deploy network functions and services. They need to manage an entire Virtual Network (VN) or infrastructure. Thus, Cloud providers should deploy dynamic and adaptive resource provisioning solutions to allocate virtual networks that reflect the time-varying needs of Cloud-hosted applications. Prior work on virtual network resource provisioning only focused on the problem of mapping the virtual nodes and links composing a virtual network request to the substrate network nodes and paths, known as the Virtual network embedding (VNE) problem. Little attention was paid to the resource management of the allocated resources to continuously meet the varying demands of embedded virtual networks and to ensure efficient substrate resource utilization. The aim of this thesis is to enable dynamic and preventive virtual network resources provisioning to deal with demand fluctuation during the virtual network lifetime, and to enhance the substrate resources usage. To reach these goals, the thesis proposes adaptive resource allocation algorithms for evolving virtual network requests. We adress the extension of an embedded virtual node requiring more resources and consider the substrate network profitability. We also deal with the bandwidth demand variation in embedded virtual links. We first provide a heuristic algorithm to deal with virtual nodes demand fluctuation. The work is extended by designing a preventive re-configuration scheme to enhance substrate network profitability. Finally, a distributed, local-view and parallel framework was devised to handle embedded virtual links bandwidth fluctuations. The approach is composed of a controller and three algorithms running in each substrate node in a distributed and parallel manner. The framework is based on the self-stabilization approach, and can manage various forms of bandwidth demand variations simultaneously
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Hajipour, Javad. "Dynamic resource allocation in buffer-aided relay-assisted cellular networks." Thesis, University of British Columbia, 2015. http://hdl.handle.net/2429/54537.
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The increasing interest in wireless connectivity to the Internet has led to new technologies in cellular networks to provide ubiquitous access to users. One of the promising solutions is to deploy wireless relays, equipped with buffers, in different parts of the cellular networks, to improve both coverage and capacity. In this thesis, the goal is to investigate resource allocation in such networks, considering different challenges, system constraints and users' service requirements. First, based on simple reasoning, analytical investigations and intuitive generalizations, we show that the use of buffers at relays improves both throughput and average end-to-end packet delay. Extensive computer simulations confirm the validity of the presented discussions and the derived results. Subsequently, we propose Channel-, Queue-, and Delay-Aware (CQDA) resource allocation policies, which provide quality of service (QoS) for both delay-sensitive and delay-tolerant users, in a multiuser orthogonal frequency division multiple access (OFDMA) network enhanced with buffering relays. Numerical results demonstrate significant improvements in providing QoS through the proposed resource allocation policies compared with the existing algorithms. Moreover, we introduce a perspective based on which we divide the network area, in a relay-assisted OFDMA system, to smaller cells served by the base station (BS) and the relays. Using convex optimization and dual decomposition, we derive closed form expressions for iterative signaling among the serving nodes to decide about resource allocation. The resulted framework provides insights for designing efficient algorithms for practical systems. Next, we introduce important parameters to be considered in the instantaneous problem formulation for data admission and resource allocation in the relay-assisted OFDMA cellular networks. Taking into account several practical constraints, we propose novel and efficient algorithms for deciding about time slot, subchannel and power allocation in a distributed manner. Numerical results confirm the effectiveness of the proposed parameters and algorithms in reaching the objectives and satisfying the constraints. Finally, we propose a novel scheduling policy, which provides queue stability and is efficient and fair in terms of delay. The proposed policy can be used in the scenarios with shared or independent channels at the BS and relays, leads to less overhead, and facilitates decentralized resource allocation.Applied Science, Faculty of
Electrical and Computer Engineering, Department of
Graduate
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Yoon, Suk-Un. "Dynamic Radio Resource Allocation in Wireless Sensor and Cognitive Radio Networks." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1259768264.
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Karakoc, Erman. "Web Service Composition Under Resource Allocation Constraints." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608309/index.pdf.
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Web service composition is an inevitable aspect of web services technology, which solves complex problems by combining available basic services and ordering them to best suit the problem requirements. Automatic composition gives us flexibility of selecting best candidate services at composition time, this would require the user to define the resource allocation constraints for selecting and composing candidate web services. Resource allocation constraints define restrictions on how to allocate resources, and scheduling under resource allocation constraints to provide proper resource allocation to tasks. In this work, web service composition system named as CWSF (Composite Web Service Framework) constructed for users to define a workflow system in which a rich set of constraints can be defined on web services. On the contrary many technologies and studies, CWSF provides a user-friendly environment for modeling web service composition system. The output of the
framework is the scheduling of web service composition in which how and when web services are executed are defined. With this work, a language, CWSL is defined to describe workflow, resource allocation constraints, selection and discovery rules of web services and associated semantic information. An important property of CWSF system is converting web service composition problem into a constraint satisfaction problem to find the best solution that meet the all criteria defined by user. Furthermore, CWSF has ability to display other possible solutions to provides users flexibility. This study also includes semantic matching and mapping facilities for service discovery.
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Damji, Navid. "Dynamic resource allocation for OFDM downlink transmission in multimedia mobile cellular systems." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=80006.
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One of the main objectives of the next generation of mobile communications is to provide cost-effective transmission of broadband multimedia services over time-varying, frequency-selective fading, band-limited wireless channels. Orthogonal Frequency Division Multiplexing (OFDM) with dynamic resource allocation is one of the potential techniques to improve the system spectral efficiency. In this work, efficient dynamic resource allocation algorithms are developed for downlink OFDM mobile cellular systems to support multimedia traffic. User channel responses are considered in the dynamic resource allocation to reduce interference and hence, to increase the system spectral efficiency while maintaining different Quality-of-Service (QoS) requirements. Performance of the proposed algorithms in terms of system throughput, fraction of satisfied users for voice, video, data and mixed services in multicell mobile communications systems is evaluated using analysis and simulation.
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Chen, Li-Wei Ph D. Massachusetts Institute of Technology. "Dynamic resource allocation in WDM networks with optical bypass and waveband switching." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/34021.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (p. 171-175).
In this thesis, we investigate network architecture from the twin perspectives of link resource allocation and node complexity in WDM optical networks Chapter 2 considers networks where the nodes have full wavelength accessibility, and investigates link resource allocation in ring networks in the form of the routing and wavelength assignment problem. In a ring network with N nodes and P calls allowed per node, we show that a necessary and sufficient lower bound on the number of wavelengths required for rearrangeably non-blocking traffic is PN/41 wavelengths. Two novel algorithms are presented: one that achieves this lower bound using at most two converters per wavelength, and a second requiring 2PN/71 wavelengths that requires significantly fewer wavelength converters. Chapter 3 begins our investigation of the role of reduced-complexity nodes in WDM networks by considering networks with optical bypass. The ring, torus, and tree architectures are considered. For the ring, an optical bypass architecture is constructed that requires the minimum number of locally-accessible wavelengths, with the remaining wavelengths bypassing all but a small number of hub nodes. The routing and wavelength assignment for all non-hub nodes is statically assigned, and these nodes do not require dynamic switching capability.
(cont.) Routing and wavelength assignment algorithms are then developed for the torus and tree architectures, and this bypass approach is extended to these topologies also. Chapter 4 continues by considering waveband routing as a second method of reducing node complexity. We consider a two-dimensional performance space using number of wavelengths and wavebands as metrics in evaluating waveband switching networks. We derive bounds for the achievable performance region based on the minimum required number of wavelengths and wavebands. We then show by construction of several algorithms that a wavelength-waveband tradeoff frontier can be achieved that compares very favorably to the bounds. Finally, Chapter 5 concludes by considering hybrid networks with both static and a dynamic wavelength provisioning. We use an asymptotic analysis where we allow the number of users in the network to become large, and via a geometric argument derive the optimal static and dynamic provisioning (in both wavelength-switched and waveband-switched scenarios) as a function of the traffic statistics to achieve non-blocking performance.
(cont.) We then extend our results to networks with a finite (possibly small) number of users where a target overflow probability is allowed. We show that by using hybrid provisioning in conjunction with waveband switching, using just a small number of switches we can obtain performance very close to a fully dynamic wavelength-switched network. %
by Li-Wei Chen.
Ph.D.
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Xu, Kuang Ph D. Massachusetts Institute of Technology. "On the power of (even a little) flexibility in dynamic resource allocation." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/91101.
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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.94
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 254-262).
Abstract We study the role of partial flexibility in large-scale dynamic resource allocation problems, in which multiple types of processing resources are used to serve multiple types of incoming demands that arrive stochastically over time. Partial flexibility refers to scenarios where (a) only a small fraction of the total processing resources is flexible, or (b) each resource is capable of serving only a small number of demand types. Two main running themes are architecture and information: the former asks how a flexible system should be structured to fully harness the benefits of flexibility, and the latter looks into how information, across the system or from the future, may critically influence performance. Overall, our results suggest that, with the right architecture, information, and decision policies, large-scale systems with partial flexibility can often vastly outperform their inflexible counterparts in terms of delay and capacity, and sometimes be almost as good as fully flexible systems. Our main findings are: 1. Flexible architectures. We show that, just like in fully flexible systems, a large capacity region and a small delay can be achieved even with very limited flexibility, where each resource is capable of serving only a vanishingly small fraction of all demand types. However, the system architecture and scheduling policy need to be chosen more carefully compared to the case of a fully flexible system. (Chapters 3 and 4.) 2. Future information in flexible systems. We show that delay performance in a partially flexible system can be significantly improved by having access to predictive information about future inputs. When future information is sufficient, we provide an optimal scheduling policy under which delay stays bounded in heavy-traffic. Conversely, we show that as soon as future information becomes insufficient, delay diverges to infinity under any policy. (Chapters 5 and 6.) 3. Decentralized partial pooling. For the family of Partial Pooling flexible architectures, first proposed and analyzed by [84], we demonstrate that a decentralized scheduling policy can achieve the same heavy-traffic delay scaling as an optimal centralized longest-queue-first policy used in prior work. This demonstrates that asymptotically optimal performance can be achieved in a partially flexible system with little information sharing. Our finding, which makes use of a new technical result concerning the limiting distribution of an M/M/1 queue fed by a superposition of input processes, strengthens the result of [84], and provides a simpler line of analysis. (Chapter 7.)
by Kuang Xu.
Ph. D.
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Kargbo, Abdulai Hassan. "An Approach to Dynamic Resource Allocation for Electric Power Disaster Response Management." Thesis, The George Washington University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10981665.
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Electricity has become an invaluable commodity for the rest of humanity such that nations irrespective of their classification in the world economy will find it difficult to function without it’s reliable supply. For nations such as the United States and the rest of the developed world, sustainable electricity supply is no longer optional. It has become a race for survival and maintenance of the very fabrics of those societies that made them who or what they are. So, whenever there is a disruption of electricity supply due to major natural disasters, the electric utility industry in the United States marshal thousands of first responders. These first responders always answer to the call of duty to face the challenge of restoring this valuable service to affected communities within the shortest possible time. In addition to the human element, electric grid restoration methods after disasters have depended mainly on the ability of intelligent electronic devices (IEDs) to communicate vital grid information with each other for system status. At one end are field devices and at the other end are human operators through outage management systems (OMS) with considerable command and control capabilities using Supervisory Control and Data Acquisition (SCADA) processes. Traditional use of centralized SCADA for system restoration during natural disasters takes too long and presents serious constrains on field workforce especially those on mutual assistance. In this study, we present a hybrid multi agent system (MAS) form of electric grid disaster response management that decentralizes the SCADA functions. The proposed system forms a Mobile Coordination and Restoration Center (MCRC) model that allows the different restoration agents the autonomy to execute restoration functions per outage demand after a disaster. The choice of agent location is modelled on the concept of Facility Location and Relocation Problem – under Uncertainty (FLRP-U) to identify optimum grid nodes that minimize distance travel and response time for field restoration crews. The model considers a dynamic approach that identifies agent locations based on outage demand changes and minimizes the total weighted distance for first responders. Using systems engineering (SE) concepts, an encompassing viewpoint is presented. The resulting architecture will examine the different agents and subsystems to help establish a technical framework that is logistical for future electric utility disaster response managers. This could be adopted by disaster managers in different settings to achieve improved restoration performance.
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Moreira, André Luis Cavalcanti. "A low complexity algorithm for dynamic fair resource allocation in OFDMA systems." Universidade Federal de Pernambuco, 2008. https://repositorio.ufpe.br/handle/123456789/1500.
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Made available in DSpace on 2014-06-12T15:50:41Z (GMT). No. of bitstreams: 1
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Previous issue date: 2008A popularização da Internet e a demanda por acesso de alta velocidade levou ao desenvolvimento da Broadband Wireless Access. Apesar do seu grande potencial, a comunicação via rádio impõe alguns desafios. Uma grande limitação é o próprio meio de transmissão devido a efeitos inerentes à propagação de radio como o path loss, frequency selective fading, espalhamento Doppler e multipath delay-spread. Nesse contexto, o OFDM é uma tecnologia promissora por causa de sua tolerância a problemas de perdas e multi-caminho. Devido à combinação de canais independentes, é possível usar diferentes modulações em cada sub-carrier, de acordo com as condições do canal. Esta técnica é conhecida como adaptive modulation and coding. Além disso, em uma arquitetura ponto a multi-ponto, múltiplos usuários podem compartilhar o espectro ao se atribuir diferentes conjuntos de sub-carriers, tirando vantagem do um efeito conhecido como diversidade multi-usuário. Em comparação com outras técnicas de múltiplo acesso, o OFDMA permite um melhor aproveitamento da diversidade multi-usuário com a possibilidade de uma alocação com alta granularidade. Muitas pesquisas têm investigado técnicas adaptativas capazes de melhorar a eficiência espectral em sistemas multi-usuário. Essas técnicas são normalmente formuladas como constraint optimization problems, conhecidos por serem NP-hard. Neste trabalho, adotamos uma abordagem heurística para lidar com esse tipo de problema. O objetivo principal é desenvolver uma estratégia de alocação fazendo uso eficiente dos recursos disponíveis e maximizando a eficiência espectral total. Entretanto, um estratégia que apenas procura maximizar a eficiência espectral pode gerar um problema relacionado à justiça no compartilhamento de recursos. Outrossim, com a popularização das redes sem fio, é esperado que elas sejam capazes de prover uma maior variedade de serviços com diferentes requisites de QoS e largura de banda. Portanto, procuramos desenvolver um algoritmo que permita ao operador da rede definir esses requisitos. De acordo com eles, o algoritmo deve fornecer o maior throughput possível dentro dos limites estabelecidos por essas restrições
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Lyazidi, Mohammed Yazid. "Dynamic resource allocation and network optimization in the Cloud Radio Access Network." Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066549/document.
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Le Cloud Radio Access Network (C-RAN) est une future direction dans les réseaux de communications sans fils pour déployer des systèmes cellulaires 4G et renforcer la migration des opérateurs vers la nouvelle génération 5G. En comparaison avec l'architecture traditionnelle des stations de base distribuées, l'architecture C-RAN apporte un lot d'avantages à l'opérateur: meilleure utilisation des ressources radio, flexibilité du réseau, minimisation de la puissance consommée et amenuisement des coûts de déploiement. Dans cette thèse, nous adressons le problème d'allocation dynamique des ressources et minimisation de la puissance des communications à liaison descendante dans le C-RAN. Notre recherche vise à allouer les ressources radio à des flux dynamiques d'utilisateurs, tout en trouvant les meilleures combinaisons entre points d'accès et unités de calculs, pour satisfaire la demande de trafic. Il s'agit en outre, d'un problème d'optimisation non linéaire et NP-difficile, comprenant plusieurs contraintes relatives aux demandes de ressources des utilisateurs, gestion d'interférences, capacités fixes des unités de calcul dans le Cloud et des liaisons de transport ainsi que la limitation de la puissance transmise maximale. Afin de surmonter la complexité inhérente à cette problématique du C-RAN, nous présentons différentes approches pour l'allocation dynamique des ressources en trois principales contributions. Les résultats de nos simulations prouvent l'efficacité de nos méthodes, comparé à celles existantes dans la littérature, en termes de taux de débit de satisfaction, nombre d'antennes actives, puissance consommée dans le Cloud, résilience et coût opérationnel du C-RANCloud Radio Access Network (C-RAN) is a future direction in wireless communications for deploying cellular radio access subsystems in current 4G and next-generation 5G networks. In the C-RAN architecture, BaseBand Units (BBUs) are located in a pool of virtual base stations, which are connected via a high-bandwidth low latency fronthaul network to Radio Remote Heads (RRHs). In comparison to standalone clusters of distributed radio base stations, C-RAN architecture provides significant benefits in terms of centralized resource pooling, network flexibility and cost savings. In this thesis, we address the problem of dynamic resource allocation and power minimization in downlink communications for C-RAN. Our research aims to allocate baseband resources to dynamic flows of mobile users, while properly assigning RRHs to BBUs to accommodate the traffic and network demands. This is a non-linear NP-hard optimization problem, which encompasses many constraints such as mobile users' resources demands, interference management, BBU pool and fronthaul links capacities, as well as maximum transmission power limitation. To overcome the high complexity involved in this problem, we present several approaches for resource allocation strategies and tackle this issue in three stages. Obtained results prove the efficiency of our proposed strategies in terms of throughput satisfaction rate, number of active RRHs, BBU pool processing power, resiliency, and operational budget cost
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Kontothanasis, Epameinondas. "Dynamic Optical Resource Allocation in Transport Networks Based on Mobile Traffic Patterns." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-207139.
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Mobile traffic increases rapidly. Based on Ericsson’s forecast [1], mobile traffic is expected to grow at a compound annual growth rate on percentage of 45% as the number of smartphone subscriptions and the consumption per subscriber increase. The monthly data traffic volume is expected to grow 6 times between 2015 and 2021. As demand increases, new technologies are investigated and deployed to cover the user requirements. Intense effort is given by researchers for the arrival of fifth generation (5G) network. High performance and increased capacity requirements drive research to heterogeneous networks. With the term “heterogeneous network”, a network that consists of different technologies and architectures is described. A heterogeneous wireless network involves the combination of macro and micro cells to improve coverage and capacity. All the traffic generated from the mobile network should be transferred from the antenna, through an access network, to the main office and from there to the backbone network. Optical networks are considered as the ideal solution for this purpose and research drives technology towards the usage of optical networks in the Fixed Mobile Convergence (FMC) architectures. The FMC architectures are proposed architectures [2] that focus to converge the fixed, mobile access and aggregation networks into a single transport network. In this study, we analyze the FMC architecture. We particularly analyze the Fronthaul architecture in combination with transport technologies such as Next Generation – Passive Optical Network 2 (NG-PON2) and Wavelength Routed Wavelength Division Multiplexing PON (WR-WDM-PON). We also take under consideration traffic patterns of mobile networks generated in various urban areas in the city of Stockholm, based in different use of land. Based on the traffic pattern, the number of small cells needed per area is calculated. In this thesis project, the traffic patterns from the mobile network and the transport network architectures are studied. The purpose of this thesis is to create an algorithm and study different sharing scenarios of the underlying transport infrastructure. The results of this algorithm will reveal if sharing and reusing resources in the transport infrastructure is beneficial in terms of saving resources.Mobiltrafik ökar snabbt. Baserat på Ericssons prognos [1], väntas mobiltrafiken få en årlig tillväxttakt på 45% i samband med att antalet smartphone-abonnemang och förbrukning per abonnent ökar. Den månatliga volymen av datatrafik väntas att öka sexfaldigt mellan 2015 och 2021. Allteftersom efterfrågan ökar, undersöks och distribueras ny teknik för att möta användarnas krav. Intensivt forskningsarbetearbete bedrivs inför av femte generationens (5G) nätverk. Högt ställda krav på prestanda och kapacitet är de drivande faktorerna i forskningen av heterogena nätverk. Med heterogena nätverk menas nätverk som består av olika teknologier och arkitekturer. Ett heterogent trådlöst nätverk involverar kombinationen av makrooch mimkroceller för att förbättra täckning och kapacitet. All trafik som genereras i mobila nätverk ska överföras från antennen, genom ett accessnät, till huvudkontoret, och därifrån till backbone-nätverket. Optiska nätverk betraktas som den idealiska lösningen för detta ändamål, och forskare driver teknologin mot användning av optiska nätverk i Fixed Mobile Convergence(FMC) arkitekturer. FMC arktekturer är föreslagna arkitekturerna som fokuserar på att konvergera fasta, mobila och aggregerings-nätverk till ett enda transportnät. I denna studie, analyserar vi FMC-arkitekturen. Vi analyserar särskilt Fronthaul-arkitekturen i kombination med transportteknologier, så som Next Generation Passive Optical Network 2 (NG-PON2) och Wavelength Routed Wavelength Division Multiplexing PON (WR-WDM-PON). Vi tar också hänsyn till trafikmönster i mobila nätverk i olika sorters urbana områden i Stockholm. Baserat på trafikmönstret räknas antalet små celler som behövs per område ut. I detta examensarbete är det trafikmönster från mobila nätverk och transportnätverksarkitekturer som studeras. Syftet med denna avhandling är att skapa en algoritm, och studera olika olika scenarion där den underliggande transportinfrastrukturens resurser delas. Resultatet av denna algoritm avslöjar om delning och återanvändning av resurser i transportnätverket är fördelaktigt när det gäller att spara resurser.
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Rojas, Cordova Alba Claudia. "Resource Allocation Decision-Making in Sequential Adaptive Clinical Trials." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/86348.
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Adaptive clinical trials for new drugs or treatment options promise substantial benefits to both the pharmaceutical industry and the patients, but complicate resource allocation decisions. In this dissertation, we focus on sequential adaptive clinical trials with binary response, which allow for early termination of drug testing for benefit or futility at interim analysis points. The option to stop the trial early enables the trial sponsor to mitigate investment risks on ineffective drugs, and to shorten the development time line of effective drugs, hence reducing expenditures and expediting patient access to these new therapies. In this setting, decision makers need to determine a testing schedule, or the number of patients to recruit at each interim analysis point, and stopping criteria that inform their decision to continue or stop the trial, considering performance measures that include drug misclassification risk, time-to-market, and expected profit. In the first manuscript, we model current practices of sequential adaptive trials, so as to quantify the magnitude of drug misclassification risk. Towards this end, we build a simulation model to realistically represent the current decision-making process, including the utilization of the triangular test, a widely implemented sequential methodology. We find that current practices lead to a high risk of incorrectly terminating the development of an effective drug, thus, to unrecoverable expenses for the sponsor, and unfulfilled patient needs. In the second manuscript, we study the sequential resource allocation decision, in terms of a testing schedule and stopping criteria, so as to quantify the impact of interim analyses on the aforementioned performance measures. Towards this end, we build a stochastic dynamic programming model, integrated with a Bayesian learning framework for updating the drug’s estimated efficacy. The resource allocation decision is characterized by endogenous uncertainty, and a trade-off between the incentive to establish that the drug is effective early on (exploitation), due to a time-decreasing market revenue, and the benefit from collecting some information on the drug’s efficacy prior to committing a large budget (exploration). We derive important structural properties of an optimal resource allocation strategy and perform a numerical study based on realistic data, and show that sequential adaptive trials with interim analyses substantially outperform traditional trials. Finally, the third manuscript integrates the first two models, and studies the benefits of an optimal resource allocation decision over current practices. Our findings indicate that our optimal testing schedules outperform different types of fixed testing schedules under both perfect and imperfect information.Ph. D.
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Avranas, Apostolos. "Resource allocation for latency sensitive wireless systems." Electronic Thesis or Diss., Institut polytechnique de Paris, 2020. http://www.theses.fr/2020IPPAT021.
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La nouvelle génération de systèmes de communication sans fil 5G vise non seulement à dépasser le débit de données du prédécesseur (LTE), mais à améliorer le système sur d'autres dimensions. Dans ce but, davantage de classes d'utilisateurs ont été introduites afin de fournir plus de choix de types de service. Chaque classe est un point différent sur le compromis entre le débit de données, la latence et la fiabilité. Maintenant, beaucoup de nouvelles applications, notamment la réalité augmentée, la conduite autonome, l'automatisation de l'industrie et la téléchirurgie, poussent vers un besoin de communications fiables avec une latence extrêmement faible. Comment gérer la couche physique afin de garantir ces services sans gaspiller des ressources précieuses et coûteuses est une question difficile. En outre, comme les latences de communication autorisées diminuent, l'utilisation d'un protocole de retransmission est contestable. Dans cette thèse, nous tentons de répondre à ces deux questions. En particulier, nous considérons un système de communication point à point, et nous voulons répondre s'il existe une allocation de ressources de puissance et de bande passante qui pourrait rendre le protocole Hybrid Automatic ReQuest (HARQ) avec n'importe quel nombre de retransmissions avantageux. Malheureusement, les exigences de très faible latence obligent à transmettre qu'un nombre limité de symboles. Par conséquent, l'utilisation de la théorie traditionnelle de Shannon est inadaptée et une autre beaucoup plus compliquée doit être employée, qui s'appelle l'analyse à bloc fini. Nous parvenons à résoudre le problème dans le cas du bruit additif blanc gaussien (AWGN) en appliquant des manipulations mathématiques et l'introduction d'un algorithme basé sur la programmation dynamique. À l'étape suivante, nous passons au cas plus général où le signal est déformé par un évanouissement de Rice. Nous étudions comment l'allocation de ressources est affectées étant donné les deux cas opposés d'informations sur l'état du canal (CSI), l'un où seules les propriétés statistiques du canal sont connues (CSI statistique), et l'autre où la valeur exacte du canal est fournie au émetteur(CSI complet).Finalement, nous posons la même question concernant le couche au-dessus, c'est-à-dire le Medium Access Control (MAC). L'allocation des ressources est maintenant effectuée sur plusieurs utilisateurs. La configuration pour chaque utilisateur reste la même, c'est-à-dire qu'une quantité précise de données doit être délivrée sous des contraintes de latence stricte et il y a toujours la possibilité d'utiliser des retransmissions. Comme la 5G classe les utilisateurs en classes d'utilisateurs différentes selon leurs besoins, nous modélisons le trafic d'utilisateurs avec le même concept. Chaque utilisateur appartient à une classe différente qui détermine sa latence et ses besoins en données. Nous développons un algorithme d'apprentissage par renforcement profond qui réussit à entraîner un modèle de réseau de neurones artificiels que nous comparons avec des méthodes conventionnelles en utilisant des algorithmes d'optimisation ou d'approches combinatoires. En fait, dans nos simulations le modèle de réseau de neurones artificiels parvient à les surpasser dans les deux cas de connaissance du canal (CSI statistique et complet)The new generation of wireless systems 5G aims not only to convincingly exceed its predecessor (LTE) data rate but to work with more dimensions. For instance, more user classes were introduced associated with different available operating points on the trade-off of data rate, latency, reliability. New applications, including augmented reality, autonomous driving, industry automation and tele-surgery, push the need for reliable communications to be carried out under extremely stringent latency constraints. How to manage the physical level in order to successfully meet those service guarantees without wasting valuable and expensive resources is a hard question. Moreover, as the permissible communication latencies shrink, allowing retransmission protocol within this limited time interval is questionable. In this thesis, we first pursue to answer those two questions. Concentrating on the physical layer and specifically on a point to point communication system, we aim to answer if there is any resource allocation of power and blocklength that will render an Hybrid Automatic ReQuest (HARQ) protocol with any number of retransmissions beneficial. Unfortunately, the short latency requirements force only a limited number of symbols to possibly be transmitted which in its turn yields the use of the traditional Shannon theory inaccurate. Hence, the more involved expression using finite blocklength theory must be employed rendering the problem substantially more complicate. We manage to solve the problem firstly for the additive white gaussian noise (AWGN) case after appropriate mathematical manipulations and the introduction of an algorithm based on dynamic programming. Later we move on the more general case where the signal is distorted by a Ricean channel fading. We investigate how the scheduling decisions are affected given the two opposite cases of Channel State Information (CSI), one where only the statistical properties of the channel is known, i.e. statistical CSI, and one where the exact value of the channel is provided to the transmitter, i.e., full CSI.Finally we ask the same question one layer above, i.e. the Medium Access Contron (MAC). The resource allocation must be performed now accross multiple users. The setup for each user remains the same, meaning that a specific amount of information must be delivered successfully under strict latency constraints within which retransmissions are allowed. As 5G categorize users to different classes users according to their needs, we model the traffic under the same concept so each user belongs to a different class defining its latency and data needs. We develop a deep reinforcement learning algorithm that manages to train a neural network model that competes conventional approaches using optimization or combinatorial algorithms. In our simulations, the neural network model actually manages to outperform them in both statistical and full CSI case
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Lazaro, de Barrio Oscar. "Dynamic radio resource management algorithms and traffic models for emerging mobile communication systems." Thesis, University of Strathclyde, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.248855.
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Griffin, Jacqueline A. "Improving health care delivery through multi-objective resource allocation." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/50108.
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This dissertation addresses resource allocation problems that occur in both public and private health care settings with the objective of characterizing the tradeoffs that occur when simultaneously incorporating multiple objectives and developing methods to address these tradeoffs. We examine three resource allocation problems (i) strategic allocation of financial resources and limited staffing capacity for the mobile delivery of health care within African countries, (ii) real-time allocation of hospital beds to internal patient requests, and (iii) development of patient redirection policies in response to limited bed availability in units within a system of hospitals. For each problem we define models, each with a different methodology, and utilize the models to develop allocation strategies that account for multiple competing objectives and examine the performance of the strategies with computational studies. In Chapter 2, we model African health care delivery systems utilizing a mixed-integer program (MIP) which accounts for financial and personnel constraints as well as infrastructure quality. We characterize tradeoffs in effectiveness, efficiency, and equity resulting from four allocation strategies with computational experiments representing the variety of spatial patterns that occur throughout the continent. The main contributions include (i) the development of a model that incorporates spatial and infrastructure characteristics and allows for a study of equity in the delivery of care, rather than access to care, and (ii) the characterization of tradeoffs in the three objectives under a variety of settings. In Chapter 3, we model the real-time assignment of bed requests to available beds as a queueing system and a Markov decision process (MDP). Through the development of bed assignment algorithms and simulation experiments, we illustrate the value of implementing strategic bed assignment practices which balance the bed management objectives of timeliness and appropriateness of assignments. The main contributions of this section include (i) the development of new bed assignment algorithms which use stochastic optimization techniques and outperform algorithms which mimic processes currently used in practice and (ii) the definition of a model and methods for the control of a large complex system that includes flexible units, multiple patient types, and type-dependent routing. In Chapter 4, we model the impact of a patient redirection policy in a hospital unit as a Markov chain. Assuming preferences for patient redirection are aligned with costs, we examine the impact of incremental changes to redirection policies on the probability of the unit being completely occupied, the long-run average utilization, and the long-run average cost of redirection. The main contributions of this chapter include (i) the introduction of a model of patient redirection with multiple patient thresholds and patient preference constraints and (ii) the definition of necessary conditions for an optimal patient redirection policy that minimizes the average cost of redirection.
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Tsai, Bing-Rong, and 蔡秉融. "Optimize Virtual CPU Resource Allocation in Virtualized Technology." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/32156068778607600183.
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碩士大同大學
資訊工程學系(所)
100
With the development of cloud computing, virtualization has become an important key technology. How to solve the resource allocation and utilization problem will be dis-cussed. In this thesis, we presents a dynamic adjustment mechanism for computing re-sources based on KVM (Kernel based Virtual Machine). This system is to improve the shortcomings of the resources allocation in traditional way, and be modified for the study DAVMCR mechanism and the DRAMS program. When system is running, using CPU SPEC technical to solve depending on the user different hardware environment to dy-namic adjust the allocation of resources. In addition, adding the optimal utilization rate of CPU let whole system to achieve load balance. Experimental result shows that by applying the proposed method can get better uti-lization rate of resources. The performance improves 34% compared to the traditional al-location program. It can also reduce the demand of the physical machines and reduce the cost of hardware maintenance. Take full advantage of the overall system resources.
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Sheng, Yu. "Dynamic Network Resource Allocation." Master's thesis, 2010. http://hdl.handle.net/10048/1419.
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A fair and optimal mechanism is required for allocating bandwidth to virtual machine migration in a WAN environment. In this thesis, we propose a dynamic resource allocation algorithm running in either centralized or distributed environments. The centralized version of our algorithm collects information from individual users and dynamically allocates bandwidth according to their demands. The distributed version of our algorithm is running on the internal nodes (e.g. routers) in the network. In the distributed case, we show that even when the routers and the users do not exchange allocation information, the allocation is still stable and optimal if the users are elastic users. Another interesting problem we solved is emergency handling, which is also critical in virtual machine live migration.
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YANG, TUNG-I., and 楊統憶. "Dynamic CPU Allocation for Docker ContainerizedMixed-Criticality Real-Time Systems." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/sx7yfs.
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碩士國立屏東大學
資訊工程學系碩士班
107
Nowadays, a Docker containerized system might run applications with different criticalities as well as timing constraints. Such a system, called Docker containerized mixed-criticality real-time system (DC-MC-RTS), consists of RT-Containers and NRT-Containers which are containers with real-time and non-real-time applications, respectively. Since Docker uses static CPU allocation methods, the performance of a DC-MC-RTS might be degraded when the workloads of containers are changed significantly at run-time. In this paper, we propose a new CPU allocation approach, called Deferrable-Server-Based Dynamic CPU Allocation Framework, to improve the performance of a DC-MC-RTS. In particular, DS-DAF first provides available CPU capacity to RT-Containers in order to ensure their timing constraints can be met. Then, the remaining CPU capacity is provided to required NRT-Containers dynamically at run-time by the deferrable server container so that their unpredictable on-line requirements could be met as much as possible. In particular, DS-DAF has a reclaiming mechanism that dynamically reclaims CPU capacity when the NRT-Containers obtained the excessive CPU capacity. We have been conducted a series of experiments for DS-DAF, and we have some encouraging results.
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Ramachandra, Girish A. "Optimal dynamic resource allocation in activity networks." 2006. http://www.lib.ncsu.edu/theses/available/etd-05182006-223103/unrestricted/etd.pdf.
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朱禾民. "Marketing Resource Allocation in Dynamic Social Networks." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/15722466414456074250.
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碩士國立彰化師範大學
資訊管理學系所
95
Viral marketing takes advantage of networks of influence among customers to inexpensively promote a product. A premise of viral marketing is that by initially targeting a few influential members of the network we can trigger a cascade of influence by which friends will recommend the product to other friends. Hence an important question is how to choose the few key individuals to use for seeding the process. In previous works, this question was investigated under the assumption of static network. In this thesis, we propose a novel approach which utilizes the concepts of genetic algorithm to find a few individuals which can maximize the spread of influence in dynamic networks. We evaluate the proposed approach by using real-world co-authorship data. The experimental results show that our approach does well at finding the few key individuals for viral marketing.
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Wang, Xinshang. "Online Algorithms for Dynamic Resource Allocation Problems." Thesis, 2017. https://doi.org/10.7916/D85H7TR6.
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Dynamic resource allocation problems are everywhere. Airlines reserve flight seats for those who purchase flight tickets. Healthcare facilities reserve appointment slots for patients who request them. Freight carriers such as motor carriers, railroad companies, and shipping companies pack containers with loads from specific origins to destinations.
We focus on optimizing such allocation problems where resources need to be assigned to customers in real time. These problems are particularly difficult to solve because they depend on random external information that unfolds gradually over time, and the number of potential solutions is overwhelming to search through by conventional methods.
In this dissertation, we propose viable allocation algorithms for industrial use, by fully leveraging data and technology to produce gains in efficiency, productivity, and usability of new systems. The first chapter presents a summary of major methodologies used in modeling and algorithm design, and how the methodologies are driven by the size of accessible data.
Chapters 2 to 5 present genuine research results of resource allocation problems that are based on Wang and Truong (2017); Wang et al. (2015); Stein et al. (2017); Wang et al. (2016). The algorithms and models cover problems in multiple industries, from a small clinic that aims to better utilize its expensive medical devices, to a technology giant that needs a cost-effective, distributed resource-allocation algorithm in order to maintain the relevance of its advertisements to hundreds of millions of consumers.
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"Techniques for Decentralized and Dynamic Resource Allocation." Doctoral diss., 2017. http://hdl.handle.net/2286/R.I.46267.
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abstract: This thesis investigates three different resource allocation problems, aiming to achieve two common goals: i) adaptivity to a fast-changing environment, ii) distribution of the computation tasks to achieve a favorable solution. The motivation for this work relies on the modern-era proliferation of sensors and devices, in the Data Acquisition Systems (DAS) layer of the Internet of Things (IoT) architecture. To avoid congestion and enable low-latency services, limits have to be imposed on the amount of decisions that can be centralized (i.e. solved in the ``cloud") and/or amount of control information that devices can exchange. This has been the motivation to develop i) a lightweight PHY Layer protocol for time synchronization and scheduling in Wireless Sensor Networks (WSNs), ii) an adaptive receiver that enables Sub-Nyquist sampling, for efficient spectrum sensing at high frequencies, and iii) an SDN-scheme for resource-sharing across different technologies and operators, to harmoniously and holistically respond to fluctuations in demands at the eNodeB' s layer.
The proposed solution for time synchronization and scheduling is a new protocol, called PulseSS, which is completely event-driven and is inspired by biological networks. The results on convergence and accuracy for locally connected networks, presented in this thesis, constitute the theoretical foundation for the protocol in terms of performance guarantee. The derived limits provided guidelines for ad-hoc solutions in the actual implementation of the protocol.
The proposed receiver for Compressive Spectrum Sensing (CSS) aims at tackling the noise folding phenomenon, e.g., the accumulation of noise from different sub-bands that are folded, prior to sampling and baseband processing, when an analog front-end aliasing mixer is utilized.
The sensing phase design has been conducted via a utility maximization approach, thus the scheme derived has been called Cognitive Utility Maximization Multiple Access (CUMMA).
The framework described in the last part of the thesis is inspired by stochastic network optimization tools and dynamics.
While convergence of the proposed approach remains an open problem, the numerical results here presented suggest the capability of the algorithm to handle traffic fluctuations across operators, while respecting different time and economic constraints.
The scheme has been named Decomposition of Infrastructure-based Dynamic Resource Allocation (DIDRA).Dissertation/Thesis
Doctoral Dissertation Electrical Engineering 2017
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Romero, Reyes Ronald. "Online Resource Allocation in Dynamic Optical Networks." 2018. https://monarch.qucosa.de/id/qucosa%3A33916.
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Konventionelle, optische Transportnetze haben die Bereitstellung von High-Speed-Konnektivität in Form von langfristig installierten Verbindungen konstanter Bitrate ermöglicht. Die Einrichtungszeiten solcher Verbindungen liegen in der Größenordnung von Wochen, da in den meisten Fällen manuelle Eingriffe erforderlich sind. Nach der Installation bleiben die Verbindungen für Monate oder Jahre aktiv. Das Aufkommen von Grid Computing und Cloud-basierten Diensten bringt neue Anforderungen mit sich, die von heutigen optischen Transportnetzen nicht mehr erfüllt werden können. Dies begründet die Notwendigkeit einer Umstellung auf dynamische, optische Netze, welche die kurzfristige Bereitstellung von Bandbreite auf Nachfrage (Bandwidth on Demand - BoD) ermöglichen. Diese Netze müssen Verbindungen mit unterschiedlichen Bitratenanforderungen, mit zufälligen Ankunfts- und Haltezeiten und stringenten Einrichtungszeiten realisieren können. Grid Computing und Cloud-basierte Dienste führen in manchen Fällen zu Verbindungsanforderungen mit Haltezeiten im Bereich von Sekunden, wobei die Einrichtungszeiten im Extremfall in der Größenordnung von Millisekunden liegen können.
Bei optischen Netzen für BoD muss der Verbindungsaufbau und -abbau, sowie das Netzmanagement ohne manuelle Eingriffe vonstattengehen. Die dafür notwendigen Technologien sind Flex-Grid-Wellenlängenmultiplexing, rekonfigurierbare optische Add / Drop-Multiplexer (ROADMs) und bandbreitenvariable, abstimmbare Transponder. Weiterhin sind Online-Ressourcenzuweisungsmechanismen erforderlich, um für jede eintreffende Verbindungsanforderung abhängig vom aktuellen Netzzustand entscheiden zu können, ob diese akzeptiert werden kann und welche Netzressourcen hierfür reserviert werden. Dies bedeutet, dass die Ressourcenzuteilung als Online-Optimierungsproblem behandelt werden muss. Die Entscheidungen sollen so getroffen werden, dass auf lange Sicht ein vorgegebenes Optimierungsziel erreicht wird. Die Ressourcenzuweisung bei dynamischen optischen Netzen lässt sich in die Teilfunktionen Routing- und Spektrumszuteilung (RSA), Verbindungsannahmekontrolle (CAC) und Dienstgütesteuerung (GoS Control) untergliedern.
In dieser Dissertation wird das Problem der Online-Ressourcenzuteilung in dynamischen optischen Netzen behandelt. Es wird die Theorie der Markov-Entscheidungsprozesse (MDP) angewendet, um die Ressourcenzuweisung als Online-Optimierungsproblem zu formulieren. Die MDP-basierte Formulierung hat zwei Vorteile. Zum einen lassen sich verschiedene Optimierungszielfunktionen realisieren (z.B. die Minimierung der Blockierungswahrscheinlichkeiten oder die Maximierung der wirtschaftlichen Erlöse). Zum anderen lässt sich die Dienstgüte von Gruppen von Verbindungen mit spezifischen Verkehrsparametern gezielt beeinflussen (und damit eine gewisse GoS-Steuerung realisieren). Um das Optimierungsproblem zu lösen, wird in der Dissertation ein schnelles, adaptives und zustandsabhängiges Verfahren vorgestellt, dass im realen Netzbetrieb rekursiv ausgeführt wird und die Teilfunktionen RSA und CAC umfasst. Damit ist das Netz in der Lage, für jede eintreffende Verbindungsanforderung eine optimale Ressourcenzuweisung zu bestimmen. Weiterhin wird in der Dissertation die Implementierung des Verfahrens unter Verwendung eines 3-Way-Handshake-Protokolls für den Verbindungsaufbau betrachtet und ein analytisches Modell vorgestellt, um die Verbindungsaufbauzeit abzuschätzen. Die Arbeit wird abgerundet durch eine Bewertung der Investitionskosten (CAPEX) von dynamischen optischen Netzen. Es werden die wichtigsten Kostenfaktoren und die Beziehung zwischen den Kosten und der Performanz des Netzes analysiert. Die Leistungsfähigkeit aller in der Arbeit vorgeschlagenen Verfahren sowie die Genauigkeit des analytischen Modells zur Bestimmung der Verbindungsaufbauzeit wird durch umfangreiche Simulationen nachgewiesen.Conventional optical transport networks have leveraged the provisioning of high-speed connectivity in the form of long-term installed, constant bit-rate connections. The setup times of such connections are in the order of weeks, given that in most cases manual installation is required. Once installed, connections remain active for months or years. The advent of grid computing and cloud-based services brings new connectivity requirements which cannot be met by the present-day optical transport network. This has raised awareness on the need for a changeover to dynamic optical networks that enable the provisioning of bandwidth on demand (BoD) in the optical domain. These networks will have to serve connections with different bit-rate requirements, with random interarrival times and durations, and with stringent setup latencies. Ongoing research has shown that grid computing and cloud-based services may in some cases request connections with holding times ranging from seconds to hours, and with setup latencies that must be in the order of milliseconds. To provide BoD, dynamic optical networks must perform connection setup, maintenance and teardown without manual labour. For that, software-configurable networks are needed that are deployed with enough capacity to automatically establish connections. Recently, network architectures have been proposed for that purpose that embrace flex-grid wavelength division multiplexing, reconfigurable optical add/drop multiplexers, and bandwidth variable and tunable transponders as the main technology drivers. To exploit the benefits of these technologies, online resource allocation methods are necessary to ensure that during network operation the installed capacity is efficiently assigned to connections. As connections may arrive and depart randomly, the traffic matrix is unknown, and hence, each connection request submitted to the network has to be processed independently. This implies that resource allocation must be tackled as an online optimization problem which for each connection request, depending on the network state, decides whether the request is admitted or rejected. If admitted, a further decision is made on which resources are assigned to the connection. The decisions are so calculated that, in the long-run, a desired performance objective is optimized. To achieve its goal, resource allocation implements control functions for routing and spectrum allocation (RSA), connection admission control (CAC), and grade of service (GoS) control. In this dissertation we tackle the problem of online resource allocation in dynamic optical networks. For that, the theory of Markov decision processes (MDP) is applied to formulate resource allocation as an online optimization problem. An MDP-based formulation has two relevant advantages. First, the problem can be solved to optimize an arbitrarily defined performance objective (e.g. minimization of blocking probability or maximization of economic revenue). Secondly, it can provide GoS control for groups of connections with different statistical properties. To solve the optimization problem, a fast, adaptive and state-dependent online algorithm is proposed to calculate a resource allocation policy. The calculation is performed recursively during network operation, and uses algorithms for RSA and CAC. The resulting policy is a course of action that instructs the network how to process each connection request. Furthermore, an implementation of the method is proposed that uses a 3-way handshake protocol for connection setup, and an analytical performance evaluation model is derived to estimate the connection setup latency. Our study is complemented by an evaluation of the capital expenditures of dynamic optical networks. The main cost drivers are identified. The performance of the methods proposed in this thesis, including the accuracy of the analytical evaluation of the connection setup latency, were evaluated by simulations. The contributions from the thesis provide a novel approach that meets the requirements envisioned for resource allocation in dynamic optical networks.