This thesis considers the problem of cross layer scheduling and radio resource allocation of multiple users in the downlink of time-slotted and frequency-slotted cellular data networks. For these networks, opportunistic scheduling algorithms improve system performance by exploiting time variations of the radio channel. Within the broader framework of opportunistic scheduling, this thesis solves three distinct problems and proposes efficient and scalable solutions for them. First, we present novel optimal and approximate opportunistic scheduling algorithms that combine channel fluctuation and user mobility information in their decision rules. The algorithms propose the use of dynamic fairness constraints. These fairness constraints adapt according to the user mobility. The optimal algorithm is an off-line algorithm that precomputes constraint values according to a known mobility model. The approximate algorithm is an on-line algorithm that relies on the future prediction of the user mobility locations in time. We show that the use of mobility information increases channel capacity. We also provide analytical bounds on the performance of the approximate algorithm. Second, this thesis presents a new opportunistic scheduling solution that maximizes the aggregate user performance subject to certain minimum and maximum performance constraints. By constraining the performance experienced by individual users, who share a common radio downlink, to some upper bounds, it is possible to provide the system operator with a better control of radio resource allocations and service differentiation among different classes of users. The proposed solution offers better performance than existing solution under practical channel conditions. Finally, we present a dynamic subcarrier allocation solution for fractional frequency reuse in multicell orthogonal frequency division multiple access systems. We formulate the subcarrier allocation as an equivalent set partitioning problem and then propose an efficient hierarchical solution which first partitions subcarriers into groups and next schedules subcarriers opportunistically to users. Simulation results for three solutions illustrate the usefulness of the proposed schemes. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

Cloud computing Infrastructure-as-a-Service (IaaS) has gained momentum in the cloud computing research field due to its ability to provide efficient infrastructures. Cloud Service Providers (CSPs) are striving to offer Quality of Service (QoS)-guaranteed IaaS services while also improving their resource utilization and maximizing profit. In addition, CSPs are challenged by the need to manipulate diverse and heterogeneous resources, realizing multiple objectives for both customers and CSPs, and handling scalability issues. These challenges are the motivations behind this work which aims at developing a multi-layered framework for constructing and managing efficient IaaS. The fundamental layer in this framework, the Virtual Infrastructure (VI) composition layer, is dedicated to composing and delivering VIs as an IaaS service. This framework relies on a preparatory step that is defined when all the available resources in the managed space are collected in a large repository, the Virtual Resource Pool (VRP). The VRP creation process unifies the representation of all the diverse and heterogeneous resources available. Subsequently, the proposed framework performs various resource allocation approaches as working solutions through the VI composition layer. These approaches adopt efficient techniques and methodologies in performing their operations. The working solutions are initiated by designing a composition approach that relies on an ontology-based model representation. The composition approach exploits semantic similarity, closeness centrality, and random walk techniques for efficient resource allocation. As a result, it provides an efficient solution in a reasonable computational time with no guarantee for the optimality of the obtained solutions. To achieve an optimal solution, the composition approach uses a mathematical modeling formulation. In this solution, the concepts of the composition approach have been integrated into a multi-objective Mixed Integer Linear Programming (MILP) model that has been solved optimally. Despite the optimality of the resulting solution, the MILP-based model restricts IaaS resource allocation to a computational running-time challenge, and the issue of limited-size datacenters. To circumvent these issues, a cost-efficient model is proposed. The new model introduces a Column Generation (CG) formulation for the IaaS resource allocation problem in large datacenters acquainted with QoS requirements. Furthermore, this formulation is realistic, adopts large-scale optimization tools that are adequate for large datacenters, and ensures optimal solutions in a reasonable time. However, growing costs in large datacenters in accordance with the growth of recent large-scale application demands, makes large datacenters economically inefficient. Thus, we advocate a distributed framework for IaaS provisioning that guarantees affordable, scalable, and QoS-assured infrastructure for hosting large-scale applications in geo-distributed datacenters. The framework incorporates two decentralized resource allocation approaches, hierarchical and distributed, that use efficient economic models. These approaches are quite promising solutions for the scalability and computational complexity issues of existing centralized approaches. Finally, the cost-efficient model has been extended to fit the distributed infrastructure by considering additional constraints that impact CSP revenue. Simulation results showcase the effectiveness of the presented work along with the potential benefits of the proposed solutions in terms of satisfying the customers’ requirements, while achieving a better resource utilization and CSP payoffs.

This thesis aims at studying the issues of economic structure and resource allocation in development. Chapter 1 provides an introduction to economic development and gives an overview of this thesis. Chapter 2 reviews some theories and models about economic structure and structural change and points out that resource allocation is a critical factor in changing the economic structure. Five characteristics of economic structure and structural change are summarized. Essay 1 in Chapter 3 investigates the relationship between competitiveness and economic growth. Adopting the Global Competitiveness Index to represent competitiveness, we empirically show that there is a two-way causal relationship between competitiveness and economic growth. We further identify that the relationship between competitiveness and economic growth change in different development stages. Specifically, better competitiveness can enhance economic growth but not vice versa in developing countries. We therefore relate such a difference to the ability to transform resources into competitiveness. This is fundamentally a question about resource allocation. Finally, we link structural change with economic growth and show that enhancing competitiveness is equivalent to improving the capacity to change the economic structure. Essay 2 in Chapter 4 studies the impacts of sub-optimal resource allocation on economic growth by applying a new model to the case of the effectiveness of official development assistance (ODA). This new model analyzes economic growth through structural change by the difference between the observed and optimal levels of competitiveness. Regarding the positive and negative impacts of foreign aid on the receiving country in the literature, we show that the net impact of ODA depends on the value of bias caused by inefficient allocation of resources and the adoption of a biased value system. As a result, both positive and negative views of ODA in the literature are somewhat correct. In principle, ODA does work in the sense of helping needy countries providing they can allocate such additional resources efficiently. The cruel truth is that most receivers of ODA are unable to transform these resources to productive uses and even lower their economic growth. The development aid country donors or global institutions may therefore have to review their existing policy for granting aid.Essay 3 in Chapter 5 introduces a new framework to study two important structural issues in China: regional fragmentation and ownership distortion. We extend the output-oriented structural efficiency measure to include subgroups to evaluate potential gains of improving resource allocation within and among subgroups. The new framework is then applied to China's industrial sector. Applying our new method for policymaking, the empirical results advocate prioritizing ownership reform over regional reform in China. Specifically, by improving resource allocation among different ownerships, outputs of the whole industrial sector can be increased by 21% of the observed level. In contrast, the potential gains of reallocating resources between western and non-western regions are less than 1%. Such a conclusion cannot be drawn from other existing models of efficiency analysis. Finally, Chapter 6 concludes the whole thesis.

No description available.

With the increase in wireless technology devices and mobile users, wireless radio spectrum is coming under strain. Networks are becoming more and more congested and free usable spectrum is running out. This creates a resource allocation problem. The resource, wireless spectrum, needs to be allocated to users in a manner such that it is utilised efficiently and fairly. The objective of this research is to find a solution to the resource allocation problem in radio networks, i.e to increase the efficiency of spectrum utilisation by making maximum use of the spectrum that is currently available through taking advantage of co-existence and exploiting interference limits. The solution proposed entails adding more secondary users (SU) on a cognitive radio network (CRN) and having them transmit simultaneously with the primary user. A typical network layout was defined for the scenario. The interference temperature limit (ITL) was exploited to allow multiple SUs to share capacity. Weighting was applied to the SUs and was based on allowable transmission power under the ITL. Thus a more highly weighted SU will be allowed to transmit at more power. The weighting can be determined by some network-defined rule. Specific models that define the behaviour of the network were then developed using queuing theory, specifically weighted processor sharing techniques. Optimisation was finally applied to the models to maximize system performance. Convex optimization was deployed to minimize the length of the queue through the power allocation ratio. The system was simulated and results for the system performance obtained. Firstly, the performance of the proposed models under the processor-sharing techniques was determined and discussed, with explanations given. Then optimisation was applied to the processor-sharing results and the performance was measured. In addition, the system performance was compared to other existing solutions that were deemed closest to the proposed models. / Dissertation (MEng)--University of Pretoria, 2017. / Electrical, Electronic and Computer Engineering / MEng / Unrestricted

In this paper, we present solutions concerning communications resource allocation for tactical communication networking. Given a mission definition (which defines communication needs among participants) and participant capabilities (such as processing power and bandwidth), algorithms are presented to determine if the mission as presented is feasible. The mathematical foundation of the problem is presented, and a "static" model to determine feasibility is shown. Further evolution of the algorithm into a "dynamic" model and the reasons for the more demanding requirements are presented. Reasoning behind use of the Netflo algorithm in the dynamic model is also discussed. The inclusion of the algorithm in a stand-alone program is discussed, including overall program structure, graphical user interface components and alternative output (such as the generation of high level network policy). Finally, future work in this area is discussed. / Master of Science

There has been a rapid growth in the data rate carried by cellular services, and this increase along with the emergence of new multimedia applications have motivated the 3rd Generation Partnership (3GPP) Project to launch Long-Term Evolution (LTE) [1]. LTE is the latest standard in the mobile network technology and is designed to meet the ubiquitous demands of next-generation mobile networks. LTE assures significant spectral and energy efficiency gains in both the uplink and down- link with low latency. Multiple access schemes such as Orthogonal Frequency Division Aultiple Access (OFDMA) and Single Carrier Frequency Division Multiple Access (SC-FDMA) which is a modified version of OFDMA have been recently adopted in 3GPP LTE downlink and uplink, respectively [1]. A typical feature of OFDMA is the decomposition of available bandwidth into multiple narrow orthogonal subcarriers. The orthogonality among subcarriers causes minimal intra-cell interference, however, the inter-cell interference (ICI) incurred on a given subcarrier is relatively impulsive and poses a fundamental challenge for the network designers. Moreover, as the number of interferers on a given subcarrier can be relatively limited it may not be accurate to model ICI as a Gaussian random variable by invoking the central limit theorem. The nature of ICI relies on a variety of indeterministic parameters which include frequency reuse factor, channel conditions, scheduling decisions, transmit power, and location of the interferers. This thesis presents a combination of algorithmic and theoretical studies for efficient modeling and management of ICI via radio resource management. In the preliminary phase, we focus on developing and analyzing the performance of several centralized and distributed interference mitigation and rate maximization algorithms. These algorithms relies on optimizing the spectrum allocation and user’s transmission powers to maximize the system capacity. Even though, the developed algorithms possesses low complexity, the simulation run-time may become challenging in the practical scenarios with very large number of users and subcarriers. Motivated by this fact, we then develop several statistical models that can accurately capture the dynamics of interference with distinct applications in the performance analysis of single carrier and multicarrier future wireless networks. The developed models can be customized for (i) various state-of-the-art coordinated and uncoordinated scheduling algorithms; (ii) slow and fast power control mechanisms; (iii) partial and fractional frequency reuse systems; and (iv) various composite fading distributions. The developed framework is useful in evaluating important system performance metrics such as outage probability, ergodic capacity, and average fairness numerically without the need of time consuming Monte-Carlo simulations. The theoretical framework is expected to enhance the planning tools for OFDMA based wireless networks by providing fast estimates of the typical performance metrics. Finally, we investigate and quantify the spectral and energy efficiency of two tier heterogeneous networks (HetNets) by employing power-control based interference mitigation technique. In particular, we analyze the performance of two tier HetNets deployment by deriving the theoretical bounds on the area spectral efficiency and exact analytical expressions for the energy efficiency by considering slow and fast power control mechanisms. The derived expressions are expected to be useful in providing insights for the design of efficient HetNet deployments.

We are living in an unjust world where the majority of humanity is subject to unequal economic and public policy systems that perpetuate cycles of poverty. Civil society, of which international NGOs are major players, are acknowledging the need for systemic, transformational change, which has to include meaningful participation in decision making processes by those whom are most vulnerable. In order to more effectively play this role, a number of international NGOs are moving decentralised structures (often comprised of independent entities at country level) to legitimately represent their primary constituents - those that are vulnerable, living in poverty, mostly in the global South. A consequence of this trajectory is added internal complexity and the creation of new management challenges, as decision making processes become more participatory and transparent. In addition, this new reality of complex federal structures also requires that power inequities between entities, are openly acknowledged and managed. Despite these challenges, this is a non-negotiable journey for many international NGOs and they acknowledge the need to adapt their management mechanisms to better handle this internal complexity. First-hand experience sparked the interest to apply operational research and system dynamics approaches to one such management mechanism, that of resource planning and allocation within international NGOs. This study aims to develop a set of insights, based on the system dynamics model, that could be useful to international NGO decision makers as they respond to their “real life” resource allocation challenges. Problem structuring methods are applied to these resource allocation challenges to gain a deeper understanding of the core components of resource allocation in order to develop a generic system dynamics model that simulates the necessary behaviours based on stakeholder input. A set of management scenarios are developed and form the basis for conducting experimental runs on the generic system dynamics model, testing different parameters in an effort to compare quantitative results. These quantitative results are used to compare performance against the original generic model, analysing trends and model behaviour to inform qualitative recommendations and conclusions.

Bibliography: leaves 215-226. / This study evaluates the costs and effectiveness of preventive and curative procedures currently available for Tuberculosis (TB) control purposes. The procedures examined are as follows : i) BCG vaccinations; ii) Secondary chemoprophylaxis; iii) Health education; iv) Mass screening campaigns; v) Investigation of contacts of infectious TB cases and symptomatic persons, i.e. suspects; and vi) Treatment regimens for notified TB patients. The analysis is largely based on data from the records of 300 randomly selected TB patients, treated at clinics in the Cape Divisional Council area in 1983. The major finding of this study is that resources available for TB control should be reallocated in the direction of secondary chemoprophylaxis, BCG vaccination administration in the Black and Coloured populations, investigation of contacts and suspects, and ambulatory treatment of notified TB patients. Conversely, vaccinating the White population, mass screening campaigns and hospitalisation of TB patients should be given relatively less emphasis in the overall TB control programme. In addition, the proportion of patients confirmed as TB cases by means of bacteriological examinations should be increased to reduce misdiagnosis.

Problems that confront the farmer are varied, but one of the most important is the combination of his possible enterprises so that maximum financial return from farming is obtained. This problem has been made more important in the last decade by the severity of the agricultural price-cost squeeze.