Engineering Commons^™

A Symbiotic Content Caching Approach In Next-Generation Information-Centric Networks Based On Game Theory, Aisha B Rahman

Electrical and Computer Engineering ETDs

The continuous growth of mobile data traffic with strict time requirements calls for the development of sustainable edge content caching solutions. This becomes more prominent in the setting of Information-Centric Networking (ICN) architectures, where different ICNs are leasing caching slices to the available content providers (CPs), who in turn offer their services to the users. In this thesis, we introduce a novel symbiotic content caching framework that provides the necessary economic benefits to the ICNs and the CPs to mutualistically collaborate among each other. The corresponding mutualistic interactions among the ICNs and CPs are studied under the prism of two …

A Bio-Inspired Alternative Positioning, Navigation, And Timing Approach Based On A Potential Game-Theoretic Model, Md Sadman Siraj

Electrical and Computer Engineering ETDs

This thesis addresses the challenge of designing of alternative Positioning, Navigation, and Timing (PNT) solutions. Inspired by the evolution of biological ecosystems, we introduce a novel symbiotic PNT solution, based on the principles of Game Theory and the exploitation of Reconfigurable Intelligent Surfaces (RISs). A set of actors, consisting of anchor nodes and RISs with known coordinates, collaborator nodes having a rough estimate of their positions, and targets of unknown positions, are cooperating to accurately determine the targets’ positioning and timing. The key objective is to minimize the estimation error of each target and collaborator node, as well as of …

Location Aware Task Offloading Framework For Edge Computing Empowered By Reconfigurable Intelligent Surfaces, Md Sahabul Hossain

Electrical and Computer Engineering ETDs

In this thesis, an energy efficient task offloading mechanism in a multi-access edge computing (MEC) environment is introduced, based on the principles of Contract Theory. The technology of Reconfigurable Intelligent Surfaces (RIS) is adopted and serves as the enabler for the energy efficient task offloading, from the perspective of location-awareness and improved communication environment. Initially a novel positioning, navigation, and timing solution is designed, based on the RIS technology and an artificial intelligent method that selects a set of RISs to perform the multilateration technique and determine the Internet of Things (IoT) nodes’ positions in an efficient and accurate manner …

Puf-Based Digital Money With Propagation-Of-Provenance And Offline Transfers Between Two Parties, Benjamin Bean, Cyrus Minwalla, Eirini Eleni Tsiropoulou, Jim Plusquellic

Electrical and Computer Engineering ETDs

Building on prior concepts of electronic money (eCash), we introduce a digital currency where a physical unclonable function (PUF) engenders devices with the twin properties of being verifiably enrolled as a member of a legitimate set of eCash devices and possessing of a hardware-based root-of-trust. A hardware-obfuscated secure enclave (HOSE) is proposed as a means of enabling a PUF-based propagation-of-provenance (POP) mechanism, which allows eCash tokens (eCt) to be securely signed and validated by recipients without incurring any third party dependencies at transfer time. The POP scheme establishes a chain of custody starting with token creation, extending through multiple bilateral …

Ai Assisted Workflows For Computational Electromagnetics And Antenna Design, Oameed Noakoasteen

Electrical and Computer Engineering ETDs

These days large volumes of data can be recorded and manipulated with relative ease. If valuable information can be extracted from them, these vast amounts of data can be a rich resource not just for the digital economy but also for scientific discovery and development of technology. When it comes to deriving valuable information from data, Machine Learning (ML) emerges as the key solution. To unlock the potential benefits of ML to science and technology, extensive research is needed to explore what algorithms are suitable and how they can be applied.

To shine light on various ways that ML can …

A Moving Target Architecture As A Side-Channel Countermeasure, Rachel M. Cazzola

Electrical and Computer Engineering ETDs

We investigate a novel side-channel attack countermeasure called Side-channel Power analysis Resistance for Encryption Algorithms using Dynamic partial reconfiguration (SPREAD). The countermeasure leverages a strategy that is best characterized as a moving target architecture. Modern field-programmable gate array (FPGA) architectures provide support for dynamic partial reconfiguration (DPR), a feature that allows real-time reconfiguration of portions of the programmable logic (PL) while the FPGA continues to carry out computing tasks. Using the Advanced Encryption Standard (AES), the proposed moving target architecture leverages DPR to change the implementation characteristics of the substitution boxes (SBOX) in real time. We present experimental hardware results …

Study Of Si-Gan Photoconductive Switches Operating Modes Using Near-Ir Radiation, Nicolas Eduardo Gonzalez Padilla

Electrical and Computer Engineering ETDs

One of the most promising solid-state devices for fast switching and radio frequency generation applications is the photoconductive switch (PCSS). These devices have been thoroughly explored since the late 1980s and exhibit remarkable switching properties in gallium arsenide (GaAs). With recent advances in wide bandgap (WBG) semiconductor manufacturing processes, there has been an increasing interest in using WBG semiconductors to implement PCSS. WBG semiconductors could exhibit the same switching characteristics as GaAs while overcoming their poor power management and short lifetime under pulsed power conditions, making PCSS a reliable option in high-power applications. Gallium Nitride (GaN) has emerged as one …

Design, Optimization, And Hardware Deployment Of A Deep Learning Model For Gps Spoofing Detection Using Gnss Satellite Receiver Protocol Data, Clarizza Morales Chacon

Electrical and Computer Engineering ETDs

The contemporary GPS infrastructure plays a vital role in advancing Position, Navigation, and Timing (PNT) applications across various sectors, including transportation, commerce, finance, and aviation. To provide a robust and authenticated infrastructure for users, it is important to develop a methodology for verifying the authenticity of satellite navigation signals, especially in civilian applications using the C/A code. This thesis explores Machine Learning (ML) techniques, focusing on the analysis of Global Navigation Satellite System (GNSS) protocol messages like UBX and NMEA to detect anomalies in receiver and satellite behavior, indicative of potential spoofing. The research demonstrates the deployment of Machine Learning …

Characterization Analysis And Design Of Mid-Wave Infrared Iii- V-Based Type-Ii Superlattice Nbn Photodetectors For Space Applications, Alexander Timothy Newell

Electrical and Computer Engineering ETDs

The performance of the mid-wave infrared InGaAs/InAsSb nBn photodetector is investigated and its viability for space applications is assessed. Three structures are grown with unique absorber layer doping profiles via molecular beam epitaxy. Material and device characterizations are performed and analyzed to determine the effects of doping on fundamental material parameters and detector performance. Noise-equivalent irradiance is calculated to be a factor of 4x that of an ideal detector exhibiting Rule 07 dark current and 100% quantum efficiency, demonstrating high sensitivity. The structures are then irradiated with 63 MeV protons to evaluate the extent of performance degradation over the course …

Dynamic Spectrum Management In 3d Networks Inspired By Biological Systems, Jordan Anthony Patrizi

Electrical and Computer Engineering ETDs

In this thesis, the challenge of dynamic spectrum management is treated following an economic-based perspective. In particular, a novel bioinspired spectrum allocation from the Network Service Providers (NSPs) to the users is introduced, exploiting the theory of symbiosis under the free competition. The overall objective is to determine the NSPs optimal bandwidth prices to maximize their profit, while satisfying the users bandwidth needs. The aforementioned spectrum management framework is analyzed while exploiting a novel 3D network architecture consisting of High Altitude Platforms (HAPs), Unmanned Aerial Vehicles (UAVs), and ground gNBs NSPs, each one of them presenting different operational characteristics and …

Enabling Intelligent Network Management Through Multi-Agent Systems: An Implementation Of Autonomous Network System, Petro Mushidi Tshakwanda

Electrical and Computer Engineering ETDs

This Ph.D. dissertation presents a pioneering Multi-Agent System (MAS) approach for intelligent network management, particularly suited for next-generation networks like 5G and 6G. The thesis is segmented into four critical parts. Firstly, it contrasts the benefits of agent-based design over traditional micro-service architectures. Secondly, it elaborates on the implementation of network service agents in Python Agent Development Environment (PADE), employing machine learning and deep learning algorithms for performance evaluation. Thirdly, a new scalable approach, Scalable and Efficient DevOps (SE-DO), is introduced to optimize agent performance in resource-constrained settings. Fourthly, the dissertation delves into Quality of Service (QoS) and Radio Resource …

Wirelessly Powering A Sea Of Sensors For Perimeter Security Applications, Ian River Chavez

Electrical and Computer Engineering ETDs

his thesis presents an innovative application of Inductive Power Transfer (IPT) technology for perimeter security systems. The approach leverages the physical properties of IPT to detect intrusions by monitoring voltage changes in wirelessly powered sensor nodes, which can double as components of an intrusion detection system. Disturbances in node orientation, indicative of potential intrusions, alter the sensor node’s resonant frequency and create measurable voltage shifts. This study explores the concept in-depth, from the analysis of resonant inductive coupling in various resonant inductive modes, to the design of transmit loops, sensor nodes, and the techniques required to ensure optimum power transfer. …

Speaker Diarization Of Noisy Classrooms From A Single Microphone Based On An Array Of Virtual Microphones And Machine Learning, Richard Briggs

Electrical and Computer Engineering ETDs

Speaker diarization from a single microphone is extremely challenging in noisy classroom environments. A new method based on simulating a microphone array has shown promising results, while requiring very little training. It used a minimum distance classifier to identify the speaker among a list of possible speakers. This thesis investigates machine learning methods for determining the speaker. The AOLME dataset that was used contains 758 samples totaling 894.4 seconds. Each is taken from a noisy classroom environment, focusing on five speakers - any one of whom could be active in a given sample - lasting an average of 1.2 seconds. …

Comparison Of Random Coupling Model To Stochastic Dyadic Green’S Function When Coupling To A Distributed Port, Evelyn Anne Dohme

Electrical and Computer Engineering ETDs

The Random Coupling Model (RCM) provides statistical representation of coupling between ports in a highly overmoded resonant cavity based on knowledge of radiation impedances of system ports and cavity properties. A recent variant of RCM, the Stochastic Dyadic Green’s Functions (S-DGF), provides the statistical distribution of fields in the cavity. By using Source Reconstruction Methods (SRM) to approximate equivalent surface currents, I hypothesized that the S-DGF can calculate the fields at their location, enabling a statistical estimate of the coupled power. Using nearfield radiation from simple patch antenna simulations and the SRM to estimate the equivalent fields and account for …

Adaptive Gps Antenna Array Beam Nulling Effectiveness Under Varying Antenna Element Positioning, Aadesh Neel

Electrical and Computer Engineering ETDs

Global Positioning System (GPS) is an essential part of modern life but is susceptible to same frequency jamming. GPS jamming can add excessive noise to a received low power signal and have the capability to change or completely distort information being sent through the GPS signal. Adaptive antenna arrays have long since been a solution to mitigating GPS jamming via beamnulling algorithms. However, there is little research on the effectiveness of these beamnulling algorithms under varying element positioning. In this work, an adaptive antenna array, consisting of Right-Hand Circularly Polarized (RHCP) nearly square GPS antenna elements, was constructed and tested …

Optimizing High-Performance Computing Design: The Impacts Of Bandwidth And Topology Across Workloads For Distributed Shared Memory Systems, Jonathan A. Milton

Electrical and Computer Engineering ETDs

With the complexity of high-performance computing designs continuously increasing, the importance of evaluating with simulation also grows. One of the key design aspects is the network architecture; topology and bandwidth greatly influence the overall performance and should be optimized. This work uses simulations written to run in the Structural Simulation Toolkit software framework to evaluate a variety of architecture configurations, identify the optimal design point based on expected workload, and evaluate the changes with increased scale. The results show that advanced topologies outperform legacy architectures justifying the additional design complexity; and that after a certain point increasing the bandwidth provides …

Progression Of Surface Flashover In Vacuum With Polymer Insulators, Kimberly M. Faris

Electrical and Computer Engineering ETDs

In pulsed power devices, an insulator is needed to isolate the transmission line from vacuum chambers. Vacuum is used as the insulator because it contains no atoms. Since it is being used as an insulator in these pulsed power insulation systems, surface flashover in vacuum is one of the most extensively studied areas since it being the greatest constraint in providing power due to dielectrics that are not able to sustain the voltage the system is operating under. These dielectrics are used in between high voltage electrodes in various pulsed power applications as electrical insulators to limit the electric current …

Data-Driven Porosity Prediction For Directed Energy Deposition, Georgia E. Kaufman

Electrical and Computer Engineering ETDs

Stochastic flaw formation leading to poor print quality is a major obstacle to the utility of directed energy deposition (DED), a laser and metal powder-based additive manufacturing technology for construction and repair of custom metal parts. While melt pool temperature variability is known to be a major factor in flaw formation, control schemes to decrease flaw formation are limited by a lack of physics-based models that fully and accurately describe DED. In this work, a stochastic reachability analysis with a data-driven model based on thermal images of the melt pool was conducted to determine the likelihood of violating melt pool …

Machine Learning Based Prediction Models For Silicon Heterojunction Solar Cell Optimization, Rahul Jaiswal

Electrical and Computer Engineering ETDs

Silicon heterojunction solar cell of Heterojunction with Thin Intrinsic Layer (HIT) structure is a commercially available technology, and its market share will significantly increase by the next decade. With such a significant market share, any minor improvement in the device’s overall efficiency can be beneficial three folds - customer return on investment, industry revenue, and the overall carbon footprint (from manufacturing to recycling/ disposing of the device). Conventionally, device optimization for solar cells has been achieved using a hit & trial approach where multiple experiments are done to evaluate the best process conditions and device parameters. This approach has some …

Energy-Efficient Operation And Performance Optimization In Computing Systems, Nafis Irtija

Electrical and Computer Engineering ETDs

In the modern world, an expansive range of computing systems are being used, and in all of these systems, energy efficiency and performance optimization are of utmost significance. But performance optimization means different things for different computing systems. Because of their difference in nature, computing systems have different requirements for efficiency and optimization. Distributed systems such as smart-grid systems, edge-computing environments, and blockchain systems focus on the behavior of the agents. Thus, the application of network economics principles, such as Game Theory and Contract Theory, can improve the operation of these systems in a multitude of ways. On the other …

Long-Term Human Video Activity Quantification In Collaborative Learning Environments, Venkatesh Jatla

Electrical and Computer Engineering ETDs

Research on video activity detection has mainly focused on identifying well-defined human activities in short video segments, often requiring large-parameter systems and extensive training datasets. This dissertation introduces a low-parameter, modular system with rapid inference capabilities, capable of being trained on limited datasets without transfer learning from large-parameter systems. The system accurately detects specific activities and associates them with students in real-life classroom videos. Additionally, an interactive web-based application is developed to visualize human activity maps over long classroom videos.

Long-term video activity detection in classrooms presents challenges, such as multiple simultaneous activities, rapid transitions, long-term occlusions, duration exceeding 15 …

Vi Energy-Efficient Memristor-Based Neuromorphic Computing Circuits And Systems For Radiation Detection Applications, Jorge Iván Canales Verdial

Electrical and Computer Engineering ETDs

Radionuclide spectroscopic sensor data is analyzed with minimal power consumption through the use of neuromorphic computing architectures. Memristor crossbars are harnessed as the computational substrate in this non-conventional computing platform and integrated with CMOS-based neurons to mimic the computational dynamics observed in the mammalian brain’s visual cortex. Functional prototypes using spiking sparse locally competitive approximations are presented. The architectures are evaluated for classification accuracy and energy efficiency. The proposed systems achieve a 90% true positive accuracy with a high-resolution detector and 86% with a low-resolution detector.

Incentives To Learn: A Location-Based Federated Learning Model, Ryan Kilpatrick-Morrison Brown

Electrical and Computer Engineering ETDs

Federated Learning (FL) effectiveness depends, among others, on the quality and quantity of the training data and process realized at the end computing nodes. In this paper, we introduce a novel location-based federated learning model, enabled by a low-cost and fast deployable Reconfigurable Intelligent Surfaces (RIS) - based approach that allows to accurately determine the distributed computing nodes’ positions. Furthermore, in order to train a global model to support different types of smart city applications, while considering two types of servers, offering a prime and common service, respectively, under different costs, the proposed location-based FL model is complemented by an …

Modeling And Characterization Of Cmos Logic Gates Under Large Signal Rf Injection, Zahra Abedi

Electrical and Computer Engineering ETDs

This research addresses the issue of electromagnetic interference (EMI) in digital electronics, which can cause undesired behavior in active electronic components and systems. As technology advances and transistor size decreases, devices become more susceptible to EMI. In addition, as voltage is scaled down to save energy, silicon chips become more susceptible to soft errors. While there are several ways to mitigate the impact of severe EMI on digital systems, minimal electromagnetic coupling can still cause significant problems. We develop analytical models to predict device upset due to EMI. The study focuses on identifying vulnerable parameters of operation related to device …

Theory, Simulation, And Experiments On A Magnetically Insulated Transmission Line Terminated By A Bremsstrahlung Diode, Troy Clay Powell

Electrical and Computer Engineering ETDs

Foundational concepts necessary for power flow analysis of a self-magnetically insulated transmission line (MITL) are introduced in theoretical form and several developments to the theory are described. These include cold-cathode electron emission physics, self-magnetic insulation physics, self-limited MITL current, and relativistic secondary ion production from anode surfaces. Modeling these physics is performed using EMPIRE, an electromagnetic particle-in-cell code.

Self-limited MITL current theory described numerically by Pointon is developed here in analytic form and is then used to drive simulations to compare to experiments that were performed in EMPIRE. Carefully calibrated current sensors from HERMES-III experiments show good agreement with EMPIRE …

A Reconfigurable Architecture For Matrix Multiplication For Low Power Applications, Jeffrey Love

Electrical and Computer Engineering ETDs

This thesis presents a hardware architecture for performing matrix multiplication via a systolic array to reduce time complexity and power consumption. The proposed architecture, the Neural Network Accelerator (NNA), was designed in Verilog HDL to perform 8-bit multiplication to reduce the resources required to implement the NNA on low-power FPGAs. The NNA’s open architecture is designed to support radiation test for fault tolerant designs targeting space applications. Commercial hardware architecture information is not public knowledge, which led us to build our own matrix multiplication architecture so that we could later study its feasibility for space applications.

The NNA was compared …

3d Speaker Geometry Inference From Digital Video Using 2d Projective Geometry, Sebastian Alonso Janampa Rojas

Electrical and Computer Engineering ETDs

The thesis discusses the need for a 3D world model reconstruction from raw video frames using 2D projective geometry. We propose a computer-aided approach to reconstructing a 3D speaker geometry from classroom videos of students learning Python.

The proposed method uses a transformer model to detect line candidates. Once the users identify lines corresponding to three orthogonal directions, the method computes the three vanishing points and the camera matrix. The method identifies the student’s mouths based on face landmark detection. After the estimates of the projections of the students’ mouths on the table are verified by the users, the proposed …

Evaluation Of The Dynamic Vision Sensor’S Photoreceptor Circuit For Infrared Event-Based Sensing, Zinah M. Alsaad

Electrical and Computer Engineering ETDs

For space surveillance applications, neuromorphic imaging is being studied as it may perform sensing and tracking tasks with less power and downstream datalink demand. The read-out of the event-based camera is made to only be sensitive to changes in the signals it receives from the photodetector, which results in a datastream of events indicating where and when changes in illumination occur. This is in contrast to the conventional framing camera, which produces images by essentially counting the electrons produced by light incident on each pixel’s photodetector. These cameras are commercially available with siliconbased detectors for applications involving visible wavelengths. However, …

Long-Term Human Participation Detection Using A Dynamic Scene Analysis Model, Wenjing Shi

Electrical and Computer Engineering ETDs

The dissertation develops new methods for assessing student participation in long (>1 hour) classroom videos. First, the dissertation introduces the use of multiple image representations based on raw RGB images and AM-FM components to detect specific student groups. Second, a dynamic scene analysis model is developed for tracking under occlusion and variable camera angles. Third, a motion vector projection system identifies instances of students talking.

The proposed methods are validated using digital videos from the Advancing Out-of-school Learning in Mathematics and Engineering (AOLME) project. The proposed methods are shown to provide better group detection, and better talking detection at …

Data-Driven Stochastic Optimal Control Using Hilbert Space Embeddings Of Distributions, Adam J. Thorpe

Electrical and Computer Engineering ETDs

Autonomous systems are increasingly being deployed in complex environments subject to real-world uncertainty. For such systems, it may be exceptionally difficult or even impossible to compute a simple mathematical model of the system--for instance due to the presence of human elements, complex mechanics or system dynamics, or learning-enabled components. Data-driven control has recently gained significant attention in this area, where observations taken from the system evolution are used to compute an implicit representation of the system that is amenable to analysis and control. However, data-driven algorithms for control present new challenges, and require new insights to enable their use. The …