Wireless Sensor Network (WSN) is a widely researched technology that has applications in a broad variety of fields ranging from medical, industrial, automotive and pharmaceutical to even office and home environments. It is composed of a network of self-organizing sensor nodes that operate in complex environments without human intervention for long periods of time. The energy available to these nodes, usually in the form of a battery, is very limited. Consequently, energy saving algorithms that maximize the network lifetime are sought-after. Link adaptation polices can significantly increase the data rate and effectively reduce energy consumption. In this sense, they have been studied for power optimization in WSNs in recent research proposals. In this thesis, we first examine the Adaptive Modulation (AM) schemes for flat-fading channels, with data rate and transmit power varied to achieve minimum energy consumption. Its variant, Adaptive Modulation with Idle mode (AMI), is also investigated. An Adaptive Sleep with Adaptive Modulation (ASAM) algorithm is then proposed to dynamically adjust the operating durations of both the transmission and sleep stages based on channel conditions in order to minimize energy consumption. Furthermore, adaptive power allocation schemes are developed to improve energy efficiency for multi-hop relay networks. Experiments indicate that a notable reduction in energy consumption can be achieved by jointly considering the data rate and the transmit power in WSNs. The proposed ASAM algorithm considerably improves node lifetime relative to AM and AMI. Channel conditions play an important role in energy consumption for both AM and ASAM protocols. In addition, the number of modulation stages is also found to substantially affect energy consumption for ASAM. Node lifetime under different profiles of traffic intensity is also investigated. The optimal power control values and optimal power allocation factors are further derived for single-hop networks and multi-hop relay networks, respectively. Results suggest that both policies are more suitable for ASAM than for AM. Finally, the link adaptation techniques are evaluated based on the power levels of commercial IEEE 802.15.4-compliant transceivers, and ASAM consistently outperforms AM and AMI in terms of energy saving, resulting in substantially longer node lifetime. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2011-02-08 18:26:29.222

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Power systems are critical infrastructures for the society. They are therefore planned and operated to provide a reliable eletricity delivery. The set of tools and methods to do so are gathered under security management and are designed to ensure that all operating constraints are fulfilled at all times. During the past decade, raising awareness about issues such as climate change, depletion of fossil fuels and energy security has triggered large investments in wind power. The limited predictability of wind power, in the form of forecast errors, pose a number of challenges for integrating wind power in power systems. This limited predictability increases the uncertainty already existing in power systems in the form of random occurrences of contingencies and load forecast errors. It is widely acknowledged that this added uncertainty due to wind power and other variable renewable energy sources will require new tools for security management as the penetration levels of these energy sources become significant. In this thesis, a set of tools for security management under uncertainty is developed. The key novelty in the proposed tools is that they build upon probabilistic descriptions, in terms of distribution functions, of the uncertainty. By considering the distribution functions of the uncertainty, the proposed tools can consider all possible future operating conditions captured in the probabilistic forecasts, as well as the likeliness of these operating conditions. By contrast, today's tools are based on the deterministic N-1 criterion that only considers one future operating condition and disregards its likelihood. Given a list of contingencies selected by the system operator and probabilitistic forecasts for the load and wind power, an operating risk is defined in this thesis as the sum of the probabilities of the pre- and post-contingency violations of the operating constraints, weighted by the probability of occurrence of the contingencies. For security assessment, this thesis proposes efficient Monte-Carlo methods to estimate the operating risk. Importance sampling is used to substantially reduce the computational time. In addition, sample-free analytical approximations are developed to quickly estimate the operating risk. For security enhancement, the analytical approximations are further embedded in an optimization problem that aims at obtaining the cheapest generation re-dispatch that ensures that the operating risk remains below a certain threshold. The proposed tools build upon approximations, developed in this thesis, of the stable feasible domain where all operating constraints are fulfilled. / <p>QC 20150508</p>

The structural vibration damping behaviour of plates and beams can be improved by the application of viscoelastic passive damping materials. Unconstrained layer damping treatments applied to metal plate systems were studied experimentally. Design and modelling of novel fibre reinforced constrained layer damping materials was performed, and implementation of these composite damping materials into laminated composite sandwich constructions commonly used as structural elements within large composite marine vessels was explored. These studies established effective methods for examining, designing and applying damping materials to metal and composite marine structures. Two test fixtures were designed and constructed to facilitate testing of viscoelastic material damping properties to ISO 6721-3 and ASTM E756. Values of material damping made in accordance with ASTM E756 over a range of temperatures were compared to values produced by a Dynamic Mechanical Analyser (DMA). Glass transition temperatures and peak damping values were found to agree well, although results deviated significantly at temperatures above the glass transition temperature. The relative influence of damping layer thickness, ambient temperature, edge conditions, plate dimensions and substrate material on the system damping performance of metal plates treated with an unconstrained viscoelastic layer was investigated experimentally. This investigation found that substrate material had the greatest influence on system damping performance, followed by damping layer thickness and plate size. Plate edge conditions were found to have little influence on the measured system damping performance. These results were dependent on the values of each variable used in the study. Modal damping behaviour of a novel fibre reinforced composite constrained layer damping material was investigated using finite element analysis and experimental methods. The material consisted of two carbon fibre reinforced polymer (CFRP) layers surrounding a viscoelastic core. Opposing complex sinusoidal fibre patterns in the CFRP face sheets were used to achieve stress-coupling by way of orthotropic anisotopy about the core. A finite element model was developed in MATLAB to determine the modal damping, displacement, stress, and strain behaviour of these complex patterned fibre constrained layer damping (CPF-CLD) materials. This model was validated using experimental results produced by modal damping measurements on CPF-CLD beam test specimens. Studies of multiple fibre pattern arrangements found that fibre pattern properties and the resulting localised material property distributions influenced modal damping performance. Inclusion of CPF-CLD materials in laminated composite sandwich geometries commonly used in marine hull and bulkhead constructions was studied experimentally. Composite sandwich beam test specimens were fabricated using materials and techniques frequently used in industry. It was found that the greatest increases in modal damping performance were achieved when the CPF-CLD materials were applied to bulkhead geometries, and were inserted within the sandwich structure, rather than being attached to the surface.

Graph traversal represents an important class of graph algorithms that is the nucleus of many large scale graph analytics applications. While improving the performance of such algorithms using GPUs has received attention, understanding and managing performance under power constraints has not yet received similar attention. This thesis first explores the power and performance characteristics of breadth first search (BFS) via measurements on a commodity GPU. We utilize this analysis to address the problem of minimizing execution time below a predefined power limit or power cap exposing key relationships between graph properties and power consumption. We modify the firmware on a commodity GPU to measure power usage and use the GPU as an experimental system to evaluate future architectural enhancements for the optimization of graph algorithms. Specifically, we propose and evaluate power management algorithms that scale i) the GPU frequency or ii) the number of active GPU compute units for a diverse set of real-world and synthetic graphs. Compared to scaling either frequency or compute units individually, our proposed schemes reduce execution time by an average of 18.64% by adjusting the configuration based on the inter- and intra-graph characteristics.

In recent years, concerns of privacy have become more prominent for social networks. Anonymizing a graph meaningfully is a challenging problem, as the original graph properties must be preserved as well as possible. We introduce a generalization of the degree anonymization problem posed by Liu and Terzi. In this problem, our goal is to anonymize a given subset of vertices in a graph while adding the fewest possible number of edges. We examine different approaches to solving the problem, one of which finds a degree-constrained subgraph to determine which edges to add within the given subset and another that uses a greedy approach that is not optimal, but is more efficient in space and time. The main contribution of this thesis is an efficient algorithm for this problem by exploring its connection with the degree-constrained subgraph problem. Our experimental results show that our algorithms perform very well on many instances of social network data. / Graduate

This thesis is a reapproachment of diverse design concepts, brought to bear upon the computer system engineering problem of identification and control of highly constrained multiprocessing (HCM) computer machines. It contributes to the area of meta/general systems methodology, and brings a new insight into the design formalisms, and results afforded by bringing together various design concepts that can be used for the construction of highly constrained computer system architectures. A unique point of view is taken by assuming the process of identification and control of HCM computer systems to be the process generated by the Activity Structures Methodology (ASM). The research in ASM has emerged from the Neuroscience research, aiming at providing the techniques for combining the diverse knowledge sources that capture the 'deep knowledge' of this application field in an effective formal and computer representable form. To apply the ASM design guidelines in the realm of the distributed computer system design, we provide new design definitions for the identification and control of such machines in terms of realisations. These realisation definitions characterise the various classes of the identification and control problem. The classes covered consist of: 1. the identification of the designer activities, 2. the identification and control of the machine's distributed structures of behaviour, 3. the identification and control of the conversational environment activities (i.e. the randomised/ adaptive activities and interactions of both the user and the machine environments), 4. the identification and control of the substrata needed for the realisation of the machine, and 5. the identification of the admissible design data, both user-oriented and machineoriented, that can force the conversational environment to act in a self-regulating manner. All extent results are considered in this context, allowing the development of both necessary conditions for machine identification in terms of their distributed behaviours as well as the substrata structures of the unknown machine and sufficient conditions in terms of experiments on the unknown machine to achieve the self-regulation behaviour. We provide a detailed description of the design and implementation of the support software tool which can be used for aiding the process of constructing effective, HCM computer systems, based on various classes of identification and control. The design data of a highly constrained system, the NUKE, are used to verify the tool logic as well as the various identification and control procedures. Possible extensions as well as future work implied by the results are considered.

This thesis is divided into two parts that each is concerned with a specific problem. The problem under consideration in the first part is to find suitable graph representations, abstractions, cost measures and algorithms for calculating placements of unmanned aerial vehicles (UAVs) such that they can keep one or several static targets under constant surveillance. Each target is kept under surveillance by a surveillance UAV, which transmits information, typically real time video, to a relay UAV. The role of the relay UAV is to retransmit the information to another relay UAV, which retransmits it again to yet another UAV. This chain of retransmission continues until the information eventually reaches an operator at a base station. When there is a single target, then all Pareto-optimal solutions, i.e. all relevant compromises between quality and the number of UAVs required, can be found using an efficient new algorithm. If there are several targets, the problem becomes a variant of the Steiner tree problem and to solve this problem we adapt an existing algorithm to find an initial tree. Once it is found, we can further improve it using a new algorithm presentedin this thesis. The second problem is optimization of time-consuming problems where the objective function is seen as a black box, where the input parameters are sent and a function valueis returned. This has the important implication that no gradient or Hessian information is available. Such problems are common when simulators are used to perform advanced calculations such as crash test simulations of cars, dynamic multibody simulations etc. It is common that a single function evaluation takes several hours. Algorithms for solving such problems can be broadly divided into direct search algorithms and model building algorithms. The first kind evaluates the objective function directly, whereas the second kind builds a model of the objective function, which is then optimized in order to find a new point where it is believed that objective function has agood value. Then the objective function is evaluated in that point. Since the objective function is very time-consuming, it is common to focus on minimizing the number of function evaluations. However, this completely disregards the possibility to perform calculations in parallel and to exploit this we investigate different ways parallelization can be used in model-building algorithms. Some of the ways to do this is to use several starting points, generate several new points in each iteration, new ways of predicting a point’s value and more. We have implemented the parallel extensions in one of the state of the art algorithms for derivative-free optimization and report results from testing on synthetic benchmarksas well as from solving real industrial problems.

In this thesis, three mesh generation software packages have been developed and implemented. The first two were based on structured mesh generation algorithms and used to solve structured surface and volume mesh generation problems of three-dimensional domains. Structured mesh generation algorithms were based on the concept of isoparametric coordinates. In structured surface mesh generation software, quadrilateral mesh elements were generated for complex three-dimensional surfaces and these elements were then triangulated in order to obtain high-quality triangular mesh elements. Structured volume mesh generation software was used to generate hexahedral mesh elements for volumes. Tetrahedral mesh elements were constructed from hexahedral elements using hexahedral node insertion method. The results, which were produced by the mesh generation algorithms, were converted to a required format in order to be saved in output files. The third software package is an unstructured quality tetrahedral mesh generator and was used to generate exact Delaunay tetrahedralizations, constrained (conforming) Delaunay tetrahedralizations and quality conforming Delaunay tetrahedralizations. Apart from the mesh generation algorithms used and implemented in this thesis, unstructured mesh generation techniques that can be used to generate quadrilateral, triangular, hexahedral and tetrahedral mesh elements were also discussed.

The aim of this thesis is to develop a methodology for obtaining an optimum configuration for the aeroballistic range models. In the design of aeroballistic range models, there are mainly three similarity requirements to be matched between the model and the actual munition: external geometry, location of the centre of gravity and the ratio of axial mass moment of inertia to the transverse mass moment of inertia. Furthermore, it is required to have a model with least possible weight, so that the required test velocities can be obtained with minimum chamber pressure and by use of minimum propellant while withstanding the enormous launch accelerations. This defines an optimization problem: to find the optimum model internal configuration and select materials to be used in the model such that the centre of gravity location and the inertia ratio are matched as closely as possible while the model withstands the launch forces and has minimum mass. To solve this problem a design methodology is devised and an optimization code is developed based on this methodology. Length, radius and end location of an optimum cylinder which has to be drilled out from the model are selected as the design variables for the optimization problem. Built&ndash / in functions from the Optimization Toolbox of Matlab&reg / are used in the optimization routine, and also a graphical user interface is designed for easy access to the design variables. The developed code is a very useful tool for the designer, although the results are not meant to be directly applied to the final product, they form the starting points for the detailed design.