Electrical & Computer Engineering Doctoral Work

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Multisine Excitation Design to Increase the Efficiency of System Identification Signal Generation and Analysis
(North Dakota State University, 2012) Schmitz, Michael J.
Reducing sample frequencies in measurement systems can save power, but reduction to the point of undersampling results in aliasing and possible signal distortion. Nonlinearities of the system under test can also lead to distortions prior to measurement. In this dissertation, a first algorithm is presented for designing multisine excitation signals that can be undersampled without distortion from the aliasing of excitation frequencies or select harmonics. Next, a second algorithm is presented for designing undersampled distributions that approximate target frequency distributions. Results for pseudo-logarithmically-spaced frequency distributions designed for undersampling without distortion from select harmonics show a considerable decrease in the required sampling frequency and an improvement in the discrete Fourier transform (DFT) bin utilization compared to similar Nyquist-sampled output signals. Specifically, DFT bin utilization is shown to improve by eleven-fold when the second algorithm is applied to a 25 tone target logarithmic-spaced frequency distribution that can be applied to a nonlinear system with 2nd and 3rd order harmonics without resulting in distortion of the excitation frequencies at the system output. This dissertation also presents a method for optimizing the generation of multisine excitation signals to allow for significant simplifications in hardware. The proposed algorithm demonstrates that a summation of square waves can sufficiently approximate a target multisine frequency distribution while simultaneously optimizing the frequency distribution to prevent corruption from some non-fundamental harmonic frequencies. Furthermore, a technique for improving the crest factor of a multisine signal composed of square waves shows superior results compared to random phase optimization, even when the set of obtainable signal phases is restricted to a limited set to further reduce hardware complexity.
Metamaterial-Inspired Reconfigurable Series-Fed Arrays
(North Dakota State University, 2014) Ijaz, Bilal
One of the biggest challenges in modern day wireless communication systems is to attain agility and provide more degrees of freedom in parameters such as frequency, radiation pattern and polarization. Existing phased array antenna technology has limitations in frequency bandwidth and scan angle. So it is important to design frequency reconfigurable antenna arrays which can provide two different frequency bandwidths with a broadside radiation pattern having a lower sidelobe and reduced frequency scanning. The reconfigurable antenna array inspired by the properties of metamaterials presented here provides a solution to attain frequency agility in a wireless communication system. The adaptive change in operating frequency is attained by using RF p-i-n diodes on the antenna array. The artificially made materials having properties of negative permeability and negative permittivity have antiparallel group and phase velocities, and, in consequence of that, they support backward wave propagation. The key idea of this work is to demonstrate that the properties of metamaterial non-radiating phase shifting transmission lines can be utilized to design a series-fed antenna array to operate at two different frequency bands with a broadside radiation pattern in both configurations. In this research, first, a design of a series-fed microstrip array with composite right/left-handed transmission lines (CRLH-TLs) is proposed. To ensure that each element in the array is driven with the same voltage phase, dual-band CRLH-TLs are adopted instead of meander-line microstrip lines to provide a compact interconnect with a zero phase-constant at the frequency of operation. Next, the work is extended to design a reconfigurable series-fed antenna array with reconfigurable metamaterial interconnects, and the expressions for array factor are derived for both switching bands.
Design and Analysis of New Printed Wideband Antennas for Wireless Applications
(North Dakota State University, 2014) Asirvatham, Koby
In this study a simple method to develop a wideband antenna is proposed. With this new technique a dipole antenna with a 48% frequency bandwidth is transformed to achieve a 120% frequency bandwidth for a voltage standing-wave ratio ≤ 2. Two different designs are tested and their performance is compared: the segmented-ring antenna and the split-ring antenna. Both antennas achieved a stable radiation pattern and a moderate gain. Nearly omnidirectional radiation patterns have been observed in both the XZ and YZ-planes. Finally, simple passive arrays are presented, demonstrating the usefulness of the split-ring antenna as an array element. Beam steering is demonstrated with a four element passive array using horizontal meandering lines. This novel antenna has wide applications in high-capacity wireless communication system.
Performance Enhancement of Pipeline ADCs
(North Dakota State University, 2014) Li, Ting
The pipeline ADC is mainstream architecture in wireless communication and digital consumer products because of its speed, resolution, dynamic performance, and power consumption. However, there are three areas of concern with the pipeline analog-to-digital converter (ADC): power consumption, accuracy, and convergence speed of the digital calibration. The traditional pipeline ADC includes a dedicated front-end sample-and-hold amplifier (SHA), which consumes a significant amount of power. This research presents a novel configuration of the front-end stage with a sample-and-hold function for a SHA-less architecture. In addition, the multi-bit front-end has multiple benefits. Interestingly, if one additional bit is resolved in the front-end stage, then the comparator offset correction ability of this stage is reduced by half. To address this problem, this research presents a novel domain-extended digital error correction algorithm to increase the comparator offset correction ability. In order to improve accuracy, a combination of techniques are used: communicated feedback-capacitor switching (CFCS), gain boost amplifiers, and low noise dynamic comparators. Here, the ADC uses the above mentioned techniques and is fabricated with AMIS 0.5 µm CMOS. The ADC, with an active area of 4.5 mm (superscript 2), consumes 264 mW when a 32 MHz input is at 75-MS/s sample rate. The third area of concern is convergence time, which determines the quality of the digital calibration. The high resolution ADC can be achieved without calibration. Therefore, in order for a digital calibration to be useful, it should minimize the analog circuits and have a reasonable convergence time. The reduced accuracy due to minimized analog circuits can be complemented by the digital calibration. Therefore, the convergence time determines the quality of the digital calibration. In this research a new domain-extended dither-based algorithm increases the convergence speed. Moreover, the novel variable-amplitude domain-extended dither-based algorithm further increases the convergence speed. Matlab simulations illustrate these improvements.
Fault Tolerant and Adaptive Systems with Focus on Networks-On-Chips
(North Dakota State University, 2014) Sajjadi Kia, Hamed
The first step in design of reliable systems is the ability to evaluate the reliability of the system. This is an important step in the process of designing reliable systems because design techniques that proactively improve the lifetime reliability of systems on chip (SoC) require some form of redundancy. The cost (area, power, and design time overheads) associated with such redundancy makes developing systems with resilience to all types of failure mechanisms impractical. To address this problem we developed an accurate reliability evaluation algorithm that is capable of identifying the vulnerable subblocks of the system. The proposed reliability evaluation methodology can also be utilized to develop a new lifetime aware floorplanning strategy that is capable of identifying the most reliable floorplan for a given design. We consider this an essential step toward a design approach where reliability is a primary objective. Recent advances in CMOS technology and integration of multiple processing elements in a single chip has also made the on chip communication a challenge in design of multi-processor SoCs (MPSoC). Networks on Chip (NoC) has been introduced as a new communication medium in response to the rising need for the new communication structure for MPSoCs. While NoC is proven to be an efficient communication structure for SoC, the same failure mechanisms and processing faults that have adverse effects on processing elements can also render NoC inoperable. We proposed a new multi layered reliable design methodology for NoCs as a hybrid solution composed of multiple layers of fault tolerant design techniques to address this challenge. The proposed structure for NoCs can address hard failures across three levels of abstraction. In first layer (software layer), we use a reliability aware mapping algorithm to assign application tasks on NoC such that network reliability is improved. In second and third layers (architecture and network-routing layers), we design an NoC architecture that uses self-repairable links and a distributed routing. The combination of these techniques in the proposed layered approach helps to provide a better performance and tradeoff between the improvement in reliability and cost due to the required redundancy and extra logic.
Network Convergence in Multicarrier Hybrid Cellular Network
(North Dakota State University, 2014) Liu, Siqian
In a multicarrier communication system with known channel state information at transmitter (CSIT), it is well-known that the water-filling power allocation scheme is optimal in achieving the Shannon capacity. However, in a multicarrier broadcast network (e.g. over-the-air TV network) without CSIT, the optimal power allocation among subcarriers is still unknown, largely due to the heterogeneity of the channel conditions associated with different receivers. In the first part of the thesis, the performance of a generic multicarrier broadcast network is thoroughly studied by exploiting the frequency diversity over subcarriers. In particular, the performance metric is first defined based on the relationship among broadcast transmission rate, coverage area and outage probability. In order to maximize the network performance, closed form expressions of the instantaneous mutual information (IMI) and the optimal power allocation schemes are derived for both low SNR and high SNR cases; upper and lower bounds are also provided to estimate broadcast coverage area in general SNR regime. Also we extend our discussion to the broadcast network with multiple collaborative transmitters. Extensive simulation results are provided to validate our analysis. In the second part of the thesis, we discuss the optimal performance of a generic broadcast cellular hybrid network. It is well known that the Dirty Paper Coding (DPC) achieves the channel capacity for multiuser degraded channels. However, the optimality of DPC remains unknown for non-degraded channel. Specifically, we derive the optimal interference pre-cancellation order for a DPC based broadcast and unicast hybrid network. Different DPC cancellation schemes are studied to maximize the hybrid capacity region. The conditions for each scheme being optimal are analytically derived. Both ergodic and outage capacity are considered as our performance metric. Our results show that the optimal interference pre-cancellation order varies with SNR and broadcast and unicast channel conditions. Moreover, in low SNR condition, the optimal power allocation scheme is derived to reach the maximal sum rate.
Efficient Message Dissemination Framework for Diverse Wireless Networks
(North Dakota State University, 2014) Khalid, Osman
Wireless networks exhibit diversity, ranging from mostly disconnected delay tolerant networks and partially connected mobile ad hoc networks, to mostly connected cellular networks. Besides having useful applications, including, vehicular communications, emergency response networks, battlefield networks, and wildlife monitoring, wireless networks face numerous challenges, such as unreliable connectivity, bandwidth restrictions, interference, frequent disruptions and delays, power outages, message loss, and malicious attacks. Moreover, when nodes are mobile, communication may be disrupted frequently for longer time periods. Designing protocols to tolerate such disruptions is challenging because of the extreme uncertainty in mobile wireless environments. Most of the existing approaches either require exact knowledge about future connectivity schedules, or perform message flooding in an attempt to improve message delivery rate. However, message flooding results in an increased overhead and loss of messages in resource constrained environments. Moreover, it is almost impossible to acquire precise future contact schedules in real-life scenarios. The goal of this dissertation is to architect robust protocols that overcome disruptions and enable applications in diverse wireless networks. We propose a suite of protocols for wireless environments where nodes transfer messages during opportunistic contacts. To conserve resources, the protocols control flooding by autonomously adapting to the changing network conditions, to find optimal temporal routes between source and destination nodes. Moreover, the dissertation presents novel approaches that utilize time-series forecasting on nodes’ contact patterns. Such routing schemes learn from nodes’ temporal contacts and mobility patterns, and forecasts the future contact opportunities among the nodes. By making precise predictions about future contacts, messages are forwarded to only those nodes that increase the message delivery likelihood. Simulation results proved that the proposed routing framework can be efficiently utilized in many real-life applications to disseminate delay tolerant data, such as electronic newspapers, weather forecasts, movie trailers, emergency information, and travel routes information in various parts of a city. The dissertation also proposes a novel application for mobile social networks that generates real-time recommendation of venues for a group of mobile users. The proposed framework utilizes Ant colony algorithm, social filtering, and hub and authority scores on the users’ contextual information to produce optimal recommendations.
Using Formal Methods to Validate the Usage, Protocols, and Feasibility in Large Scale Computing Systems
(North Dakota State University, 2014) Malik, Saif Ur Rehman
A paradigm shift has occurred in the Information and Communication Technology sector. The main obstacle to relegate complex and sensitive tasks is not the inadequate speed and unsatisfactory computing power of the existing machines. However, the inability to design and implement the systems, with a desirable degree of confidence in the correctness and reliability, under different circumstances, has crept in to be the primary concerns in achieving high performance. The hardware and software systems are growing inevitably in scale and functionality, such as cloud computing systems and Data Center (DC). In the said perspective, the complexity of the systems is also increasing. The likelihood of elusive errors is directly proportional to the complexity of the systems that also increase the cost of errors while the systems are operational. In large scale systems the density of computational devices is in order of tens of thousands of servers. Moreover, the effects of errors and miscalculations are substantial. Furthermore, if the specified quality of service is not delivered by the cloud service providers, then the reputation may fall down and users will not use the services, resulting in huge financial lose. Therefore, the reliability, robustness, and availability of systems are very essential. In the said perspective, to increase the reliability and correctness of the systems, we propose the use of Formal Methods (FM). The FM use sound mathematical foundations to prove program correctness. The aim of our research is to deploy various FM tools and techniques to formally analyze the behavior and correctness of the strategies, such as routing algorithms and virtualization models that are implemented in large scale computing systems. The goal of our research is to thoroughly study the strategies, highlight the grey areas that can be further exploit to increase the reliability and performance, and propose a feasible solution. The large scale computing systems, specifically DC exhibits different architectural characteristics, such as predefined complex architectural and topological pattern composed in different layers. The aforementioned characteristics of the underlying network along with the large scale of the servers situate several challenges for the adoption of FMs strategies.
Analysis and Characterization of Cloud Based Data Center Architectures for Performance, Robustness, Energy Efficiency, and Thermal Uniformity
(North Dakota State University, 2014) Bilal, Kashif
Cloud computing is anticipated to revolutionize the Information and Communication Technology (ICT) sector and has been a mainstream of research over the last decade. Today, the contemporary society relies more than ever on the Internet and cloud computing. However, the advent and enormous adoption of cloud computing paradigm in various domains of human life also brings numerous challenges to cloud providers and research community. Data Centers (DCs) constitute the structural and operational foundations of cloud computing platforms. The legacy DC architectures are inadequate to accommodate the enormous adoption and increasing resource demands of cloud computing. The scalability, high cross-section bandwidth, Quality of Service (QoS) guarantees, privacy, and Service Level Agreement (SLA) assurance are some of the major challenges faced by today’s cloud DC architectures. Similarly, reliability and robustness are among the mandatory features of cloud paradigm to handle the workload perturbations, hardware failures, and intentional attacks. The concerns about the environmental impacts, energy demands, and electricity costs of cloud DCs are intensifying. Energy efficiency is one of mandatory features of today’s DCs. Considering the paramount importance of characterization and performance analysis of the cloud based DCs, we analyze the robustness and performance of the state-of-the-art DC architectures and highlight the advantages and drawbacks of such DC architecture. Moreover, we highlight the potentials and techniques that can be used to achieve energy efficiency and propose an energy efficient DC scheduling strategy based on a real DC workload analysis. Thermal uniformity within the DC also brings energy savings. Therefore, we propose thermal-aware scheduling policies to deliver the thermal uniformity within the DC to ensure the hardware reliability, elimination of hot spots, and reduction in power consumed by cooling infrastructure. One of the salient contributions of our work is to deliver the handy and adaptable experimentation tools and simulators for the research community. We develop two discrete event simulators for the DC research community: (a) for the detailed DC network analysis under various configurations, network loads, and traffic patterns, and (b) a cloud scheduler to analyze and compare various scheduling strategies and their thermal impact.
Contextualization in Large-Scale Social Networks
(North Dakota State University, 2014) Irfan, Rizwana S.
Social computing-based applications provide a coherent medium through which people can be interactive and socialize by developing a Web-based communication channel that integrates different Social Networking Services (SNSs) in the Social Networking Platforms (SNPs). Different SNSs, such as photo, audio, and video sharing, have emerged as an essential resources for the dissemination of information about the human interaction patterns. Most of the SNSs are integrated into a comprehensive and coherent paradigm called the Social Networking Platform (SNP). Most of the existing SNSs focused on content-based, media-based, and geo-location-based approach. The content-based SNSs allow the text-based interactions among individuals, such as communities, blogs, and social news. The media-based SNSs provide the social interaction through various multimedia formats, such as video and audio. Geo-location-based SNSs provide location-based social communication. However, all of the aforementioned techniques lack the semantic analysis which is the most integral and crucial part of the true understanding. The goal of this dissertation is to incorporate the existing SNSs into the context-enriched information that provide the services customization based on the individual human characteristics, such as human preferences, and emotions. The computer interactive infrastructure can be enriched by leveraging information about the users’ personal context (profile, preferences, attitude, and habits) that provides sophisticated context-aware services, such as semantic-based search and context-aware recommendations. The dissertation proposes MobiContext, a cloud-based Bi-Objective Recommendation Framework (BORF) for mobile social networks that generates real-time recommendation of venues for a group of mobile users. The MobiContext utilizes multi-objective optimization techniques to generate personalized recommendations. To address the issues pertaining to cold start and data sparseness, the BORF performs data preprocessing by using the Hub-Average (HA) inference model. Moreover, the Weighted Sum Approach (WSA) is implemented for scalar optimization and an evolutionary algorithm (NSGA-II) is applied for vector optimization to provide optimal suggestions to the users about a venue. The dissertation also proposes a SocialRec, a context-aware recommendation framework that utilizes a rating sentiment inference approach to incorporate textual users’ review into traditional collaborative filtering methods for personalized recommendations. The proposed framework utilizes semantic analysis scores on the users’ contextual information to produce optimal recommendations.
Zeroth Order Resonator (ZOR) Based RFID Antenna Design
(North Dakota State University, 2014) Masud, Muhammad Mubeen
Meander-line and multi-layer antennas have been used extensively to design compact UHF radio frequency identification (RFID) tags; however the overall size reduction of meander-line antennas is limited by the amount of parasitic inductance that can be introduced by each meander-line segment, and multi-layer antennas can be too costly. In this study, a new compact antenna topology for passive UHF RFID tags based on zeroth order resonant (ZOR) design techniques is presented. The antenna consists of lossy coplanar conductors and either inter-connected inter-digital capacitor (IDC) or shunt inductor unit-cells with a ZOR frequency near the operating frequency of the antenna. Setting the ZOR frequency near the operating frequency is a key component in the design process because the unit-cells chosen for the design are inductive at the operating frequency. This makes the unit-cells very useful for antenna miniaturization. These new designs in this work have several benefits: the coplanar layout can be printed on a single layer, matching inductive loops that reduce antenna efficiency are not required and ZOR analysis can be used for the design. Finally, for validation, prototype antennas are designed, fabricated and tested.
A New Methodology for the Design and Tuning of Robust PID Controllers in Electric Drives
(North Dakota State University, 2014) Mehmood, Chaudhry Arshad
AC induction motor-drive systems are the backbone for numerous industrial applications, such as aerospace, medical equipment, and nuclear power plants. The control performance of electric drives is sensitive to several uncontrollable disturbances from changes in ambient conditions in the form of machine parameter variations such as: magnetizing inductance (Lm), and rotor resistance (Rr). Such variations may trigger instability because of mismatch between the reference and desired conditions. The most common techniques to solve the issue are: (a) gain adaptation that requires instrumentation to monitor system, (b) nonlinear control methods, such as sliding mode, feedback linearization, and (c) robust control method, such as H∞, and μ-analysis to account for motor uncertainties. Despite the prevalence of PID controllers, a systematic method to tune their parameters to ensure robustness remains an open problem. In this dissertation, a systematic method to tune PI controllers while factoring uncertainties is developed. Two major design methods are proposed: (a) based on Kharitonov’s theorem and (b) based on fractional order controllers. In (a), the control design problem for AC drives can be cast into as a set of interval polynomials that can be analyzed via Kharitonov’s theorem. Also proposed a method to solve the resulting polynomials, which then yield the controller coefficients. In (b), we show how fractional order controllers (FrOC)-a generalization of PID that consider fractional values for the integral and derivative coefficients can be designed to achieve our main objectives. A unique advantage of such controllers is the so-called isodamping property (constant phase) and robustness. The performance of controllers is assessed by comparing them with two well established techniques: traditional method based on gain/phase margin requirements, and symmetric optimum techniques an industrially popular technique that requires constant gain over a desired bandwidth. While both these techniques use reduced order models, the proposed methods are advantageous because they can handle the full model of the machine. The simulation results suggest that the proposed controllers remain robust against the chosen uncertainties while both traditionally designed controllers succumb to instability. The work paves a novel way for the design and tuning of robust PID controllers in electric drives.
Adaptive Beamforming for Antennas on General Wedge- and Cylindrical-Shaped Surfaces
(North Dakota State University, 2014) Irfanullah, Irfanullah
Adaptive beamforming antennas capable of accommodating the growing number of wireless subscribers throughout the world has become an essential part of modern wireless systems. In this work, the beamforming of a conformal antenna on a changing conformal surface is studied by relating the varying position of each antenna element in the array to the weighting coefficients (i.e, array weights) required to give a desired antenna beam formation. In particular, the beamforming of a 1 x 4 array on a changing wedge- and cylindrical-shaped surface is studied using the projection method on a wavefront of a transmitted wave in a particular direction. To validate the theory, a 1 x 4 prototype antenna with individual voltage-controlled phase shifters and attenuators is used to implement the computed weights of each individual antenna element for measurements in an anechoic chamber. Overall agreement between theory, simulations and measurements is shown throughout the work. Furthermore, the effects of mutual coupling and changing conformal surfaces on the behavior of the beamforming pattern and array weights is investigated and summarized.
A Metamaterial-Based Multiband Phase Shifter
(North Dakota State University, 2014) Maassel, Michael
A design methodology for a multi-band phase shifter using a metamaterial-based transmission line was developed. This method is different in that the loaded-line phase shifter has a phase shift of 90 degrees at the center frequencies of both bands instead of -90 degrees and -270 degrees. The method was validated using simulation and measured results.
A Compact Cylindrical-Shape Microstrip Structure with Cloaking Properties for Mutual Coupling Reduction in Array Antennas
(North Dakota State University, 2014) Naqvi, Syed Aftab
A cylindrical-shaped microstrip structure with cloaking properties is presented as a shielding device to reduce the mutual coupling between two patch antennas. The surface comprises of a number of 2-port microstrip (2-PM) elements printed on individual substrates and, to enclose a particular region, several 2-PM elements are interconnected into a cylindrical shape. Each 2-PM element has the capability of coupling an incident EM field on the surface to the adjacent interconnected elements. Then, because the 2-PM elements are connected into a cylindrical shape, the incident EM field is re-radiated from the other interconnected 2-PM elements in a direction away from the transmitter; achieving a behavior similar to a cloak. The prototypes in this dissertation illustrates that this surface has the additional benefit of overcoming many of the manufacturing difficulties of traditional cloaks because microstrip structures are used. To demonstrate this concept, a cylindrical surface operating at 3.89 GHz and a frequency reconfigurable surface (consisting of 2-port frequency reconfigurable microstrip elements (2-PFRM)) operating at 3.68 GHz and 3.89 GHz is simulated in HFSS, manufactured and measured in a full anechoic chamber. Moreover, as an application, the cylindrical surface operating at 3.89 GHz is used to reduce the mutual coupling between two patch antennas operating simultaneously at 3.89 GHz. The radiation pattern and the gain of a 2-element array is measured to demonstrate the negligible effects of a cylindrical surface on the far field antenna array parameters. Simulation and measurement results are in good agreement and validate the proposed EM cloak-based surface for applications such as antenna array shielding, radar cross section and communications in complex EM environments.
Utilizing Recommender Systems as an Analysis Tool for Measuring Network Dynamics
(North Dakota State University, 2015) Usman Shahid Khan, Muhammad
Recommender systems apply numerous knowledge discovery techniques to suggest the preferred products, information, or service on contextual data. In our study, we utilize the recommender system for analyzing and measuring the network dynamics. The dynamic factors such as change in network shape or data size affect the performance of the networks and make it harder for the optimization techniques to be used for finding the optimum solution. In our research, we focused on the monitoring and analyzing the dynamic factors involved in two networks: (a) body area networks and (b) road networks; and based on the study proposed the efficient solution for mitigating the negative effects of the dynamic factors involved using recommender systems. In body area networks, we monitored the dynamically changing body area sensors data and studied the correlation between the sensors’ location and activity recognition. We proposed a cloud based framework that has employed a feature descriptor called Local Energy-based Shape Histogram (LESH) to preserve the maximum information of local energy. We have also used the Wearable Action Recognition Database (WARD) dataset to perform the experiments. Based on our study we proposed the best combination of sensors for various activities recognition. In road networks, we monitored the congestion during large-scale emergency evacuation and proposed efficient route recommendation service that helps in fast and safe evacuation. To respond to emergencies in a fast and an effective manner, it is of critical importance to have efficient evacuation plans that lead to minimum road congestion. The existing approaches, mostly based on multi-objective optimizations, are not scalable enough when involve numerous time varying parameters, such as traffic volume, safety status, and weather conditions. In this study, we propose a new scalable emergency evacuation service that recommends the evacuees with the most preferred routes towards safe locations during a disaster. The evacuees are directed towards those routes that are safe and have least congestion resulting in decreased evacuation time. The results indicated the improved efficiency of our service for average evacuation times and evacuation delays.
Perceptual Video Quality Model and its Application in Wireless Multimedia Communications
(North Dakota State University, 2015) Hameed, Abdul
With the exponential growth of video traffic over wireless networked and embedded devices such as mobile phones and sensors, mechanisms are needed to predict the perceptual quality of video in real time and with low complexity, based on which networking protocols can control video quality and optimize network resources to meet the quality of experience requirements of users. This thesis is composed of three related pieces of work. In the first piece of work, an efficient and light-weight video quality prediction model through partial parsing of compressed from the H.264/AVC compressed bitstream is proposed. A set of features were introduced to reflect video content characteristics and distortions caused by compression and transmission and were obtained directly in parsing mode without decoding the pixel information in macro-blocks. Based on the features, an artificial neural network model was trained for perceptual quality prediction. In the second piece of work, a perceptual video quality prediction model is trained based on massive subjective test results. Prediction of perceptual quality is achieved through a decision tree using a set of easily calculated features from the compressed bitstream and the network. Moreover, based on the prediction model, a novel Forward Error Correction (FEC) scheme is introduced to protect video packets by taking into consideration video content characteristics, compression parameters, as well as network condition. Given a perceptual quality requirement, the error control scheme adjusts the level of protection for different components in a video stream such that the network overhead needed for transmission is minimized. In the third piece of work, a study was conducted to examine whether the previous prediction model could provide a good confidence measure in a different domain of judgments. The accuracy of judgements demonstrated the predictive validity of confidence measure with respect packet loss ratio traits. The results of this study were consistent with the previous one and the experiments suggested that brief and evaluative thin slice judgments are made relatively intuitively. Present research represents a new entry into the domain of high level judgments, such as video confidence measure by the use of our existing perception quality model.
Characterization of a Structure Consisting of Magnetostatic Responsive Microscopic Particles and Its Applications In Antennas
(North Dakota State University, 2015) Iftikhar, Adnan
Wireless communication systems often require that a single antenna work at different frequencies. Thus the recon gurable antennas are useful in frequency agile environments to receive a signal over multiple bands. Research on antenna recon gurability using mechanical systems and radio frequency (RF) switches have been implemented in the past years. One problem for these voltage- controlled switches is that they require direct current (DC) bias control lines for operation. The incorporation of DC biasing circuitry also limits designers to explore the recon gurable capacity of many antennas. The DC bias control lines can possibly degrade the antenna performance. Moreover, because of the additional control signals, many existing multiband systems cannot use recon gurable antennas. In this research, magnetostatic responsive particles are used in micro-sized cavities to manufacture novel magnetic switches that are activated in a magnetic eld. Furthermore, the characterization, modeling in simulation software, and lumped element model extraction of these micro electromechanical systems (MEMS) based on magnetic switches is presented. A re ned method of quantifying the micro sized magnetic particles in a cavity and the response of the proposed micro level magnetic switches in the RF eld is also explained in detail. Then, a microstrip patch antenna loaded with Electromagnetic Band Gaps (EBGs) that cannot be recon gured using existing RF switching devices was recon gured using the proposed magnetic switches and is presented in this research for the rst time. A comparison between PIN diodes and the proposed magnetic switches on a microstrip patch is also included in this research to show the efficiency of the proposed structure. Overall, the proposed magnetic switches showed good results when used in antenna systems to achieve recon gurability and do not effect the radiation characteristics of the recon gured antenna.
Energy Efficient Data Centers for On-Demand Cloud Services
(North Dakota State University, 2015) Jawad, Muhammad
The primary objective of the Data Centers (DCs) is to provide in-time services to the cloud customers. For in-time services, DCs required an uninterruptable power supply at low cost. The DCs’ power supply is directly linked with the stability and steady-state performance of the power system under faults and disturbances. Smart Grids (SGs) also known as the next generation power systems utilize communication and information technology to optimize power generation, distribution, and consumption. Therefore, it is beneficial to run DCs under SG environment. We present a thorough study of the wide area smart grid architecture, design, network, and control. The goal was to familiarize with the smart grid operation, monitoring, and control. We analyze different control mechanisms proposed in the past to study the behavior of the wide area smart grid symmetric and asymmetric grid faults conditions. The Study of the SG architecture was a first step to design power management and energy cost reduction models for the DC running under SGs. At first, we present a Power Management Model (PMM) for the DCs to estimate energy consumption cost. The PMM is a comprehensive model that considers many important quantities into account, such as DC power consumption, data center battery bank charging/discharging, backup generation operation during power outages, and power transactions between the main grid and the SG. Second, renewable energy, such as wind energy is integrated with the SG to minimize DC energy consumption cost. Third, forecasting algorithms are introduced in the PMM to predict DC power consumption, wind energy generation, and main grid power availability for the SG. The forecasting algorithms are employed for day-ahead and week-ahead prediction horizons. The purpose of the forecasting algorithms is to manage power generation and consumption, and reduce energy prices. Fourth, we formulate chargeback model for the DC customers to calculate on-demand cloud services cost. The DC energy consumption cost estimated through PMM is integrated with the other operational and capital expenditures to calculate per server utilization cost for the DC customers. Finally, the effectiveness of the proposed models is evaluated on real-world data sets.
Energy Efficient Resource Scheduling Methodologies for Cluster and Cloud Computing
(North Dakota State University, 2015) Fayyaz, Ahmad
One of the major challenges in the High Performance Computing (HPC) clusters, Data Centers, and Cloud Computing paradigms is intelligent power management to improve energy efficiency. The key contribution of the presented work is the modeling of a Power Aware Job Scheduler (PAJS) for HPC clusters, such that the: (a) threshold voltage is adjusted judiciously to achieve energy efficiency and (b) response time is minimized by scaling the supply voltage. The key novelty in our work is utilization of the Dynamic Threshold-Voltage Scaling (DTVS) for the reduction of cumulative power utilized by each node in the cluster. Moreover, to enhance the performance of the resource scheduling strategies in first part of the work, independent tasks within a job are scheduled to most suitable Computing Nodes (CNs). First, our research analyzes and compares eight scheduling techniques in terms of energy consumption and makespan. Primarily, the most suitable Dynamic Voltage Scaling (DVS) level adhering to the deadline is identified for each of the CNs by the scheduling heuristics. Afterwards, the DTVS is employed to scale down the static, as well as dynamic power by regulating the supply and bias voltages. Finally, the per node threshold scaling is used attain power saving. Our simulation results affirm that the proposed methodology significantly reduces the energy consumption using the DTVS. The work is further extended and the effect of task consolidation is studied and analyzed. By consolidating the tasks on a fewer number of servers the overall power consumed can be significantly reduced. The tasks are first allocated to suitable servers until all the tasks are exhausted. The idle servers are then turned off by using DTVS. The Virtual Machine (VM) monitor checks for under-utilized, partially filled, over-utilized, and empty servers. The VM monitor then migrates the tasks to suitable servers for execution if a set of conditions is met. By this way, many servers those were under-utilized get free and are turned off by using DTVS to save power. Simulations results confirm our study and a substantial reduction in the overall power consumption of the cloud data center is observed.

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