In the context of a system design, resource-constraints refer to severe restrictions on allowable resources, while resource-efficiency is the capability to achieve a desired performance and, at the same time, to reduce wasting resources. To design for low-cost platforms, these fundamental concepts are useful under different scenarios and they call for different approaches, yet they are often mixed. Resource-constrained systems require aggressive optimizations, even at the expense of performance, to meet the stringent resource limitations. On the other hand, resource-efficient systems need a careful trade-off between resources and performance, to achieve the best possible combination. Designing systems for resource-constraints with the optimizations for resource-efficiency, or vice versa, can result in a suboptimal solution. Using modern cryptographic applications as the driving domain, I first distinguish resource-constraints from resource-efficiency. Then, I introduce the recurring strategies to handle these cases and apply them on modern cryptosystem designs. I illustrate that by clarifying the application context, and then by using appropriate strategies, it is possible to push the envelope on what is perceived as achievable, by up to two orders-of-magnitude. In the first part of this dissertation, I focus on resource-constrained modern cryptosystems. The driving application is Physical Unclonable Function (PUF) based symmetric-key authentication. I first propose the smallest block cipher in 128-bit security level. Then, I show how to systematically extend this design into the smallest application-specific instruction set processor for PUF-based authentication protocols. I conclude this part by proposing a compact method to combine multiple PUF components within a system into a single device identifier. In the second part of this dissertation, I focus on resource-efficient modern cryptosystems. The driving application is post-quantum public-key schemes. I first demonstrate energy-efficient computing techniques for post-quantum digital signatures. Then, I propose an area-efficient partitioning and a Hardware/Software codesign for its implementation. The results of these implemented modern cryptosystems validate the advantage of my approach by quantifying the drastic improvements over the previous best. / Ph. D.

The quick growth of embedded systems and their increasing computing power has made them suitable for a wider range of applications. Despite the increasing performance of modern embedded processors, they are outpaced by computational demands of the growing number of modern applications. This trend has led to emergence of hardware accelerators in embedded systems. While the processing power of dedicated hardware modules seems appealing, they require significant effort of development and integration to gain performance benefit. Thus, it is prudent to investigate and estimate the integration overhead and consequently the hardware acceleration benefit before committing to implementation. In this work, we present FPGA-Roofline, a visual model that offers insights to designers and developers to have realistic expectations of their system and that enables them to do their design and analysis in a faster and more efficient fashion. FPGA-Roofline allows simultaneous analysis of communication and computation resources in FPGA-based hardware accelerators. To demonstrate the effectiveness of our model, we have implemented hardware accelerators in FPGA and used our model to analyze and optimize the overall system performance. We show how the same methodology can be applied to the design process of any FPGA-based hardware accelerator to increase productivity and give insights to improve performance and resource utilization by finding the optimal operating point of the system. / Master of Science

Internet of Things require a continuous power supply for longevity and energy harvesting from ambient sources enable sustainable operation of such embedded devices. Using selfpowered power supply gives raise two scenarios, where there is surplus or scarce harvested energy. In situations where the harvester is capable of harvesting beyond its storage capacity, the surplus energy is wasted. In situations where the harvester does not have sufficient resources, the sparse harvested energy can only transiently power the device. Transiently powered devices, referred to as intermittent computing devices, ensure forward progress by storing checkpoints of the device state at regular intervals. Irrespective of the availability of energy, the device should have adequate security. This thesis addresses the security of energy harvested embedded devices in both energy scenarios. First, we propose precomputation, an optimization technique, that utilizes the surplus energy. We study two cryptographic applications, namely bulk encryption and true random number generation, and we show that precomputing improves energy efficiency and algorithm latency in both applications. Second, we analyze the security pitfalls in transiently powered devices. To secure transiently powered devices, we propose the Secure Intermittent Computing Protocol. The protocol provides continuity to underlying application, atomicity to protocol operations and detects replay and tampering of checkpoints. Both the proposals together provide comprehensive security to self-powered embedded devices. / Master of Science / Internet of Things(IoT) is a collection of interconnected devices which collects data from its surrounding environment. The data collected from these devices enable emerging technologies like smart home and smart cities, where objects are controlled remotely. With the increase in the number of such devices, there is a demand for self-powered devices to conserve electrical energy. Energy harvesters are suitable for this purpose because they convert ambient energy into electrical energy to be stored in an energy buffer, which is to be used when required by the device. Using energy harvesters as power supply presents us with two scenarios. First, when there is sufficient ambient energy, the surplus energy, which is the energy harvested beyond the storage capacity of the buffer, is not consumed by the device and thus, wasted. Second, when the harvested energy is scarce, the device is forced to shutdown due to lack of power. In this thesis, we consider the overall security of an energy harvested IoT device in both energy scenarios. We optimize cryptographic algorithms to utilize the surplus energy and design a secure protocol to protect the device when the energy is scarce. Utilizing both the ideas together provides adequate security to the Internet of Things.

No description available.

This thesis describes the implementation of zero-cost auto-tuning techniques for embedded Proportional Integral and Derivative (PID) controllers, specifically focusing on their application in the control of proportional valves within Micro Gas Chromatography (uGC) systems. uGC systems are miniaturized versions of conventional GC systems, and require precise temperature, flow and pressure control for the micro-fabricated preconcentrators and micro columns. PID controllers are widely used in process control applications due to their simplicity and effectiveness. The Commercial Off The Shelf (COTS) available controllers are expensive, bulky, need system compatibility and have high lead times. The proposed auto-tuner features simple Python-implemented empirical calculations based on Ziegler Nichols relay-based PID tuning method to determine the optimal PID gains. Leveraging Wi-Fi the system enables tuning for any embedded platform while visualizing transient response through the Graphical User Interface (GUI). The embedded-GUI interface provides a customizable auto-tuning experience extending usage across diverse temperature, pressure and flow regulation applications in environmental analysis. Specifically for uGC systems, the GUI integrates with existing hardware stack using minor software enhancements to enable rapid, automated PID tuning for thermal and flow control applications. The performance is analyzed by evaluating response metrics including overshoot, rise time, and steady-state error. / Master of Science / Commercially available flow and thermal regulators are expensive and bulky. In applications like micro gas chromatography (uGC) systems, these commercial tools to regulate actuator control reduce portability and may require different regulators for different control ranges. To overcome these challenges, we developed an open-source, transparent Proportional-Integral-Derivative (PID) auto-tuner for micro-electromechanical systems (MEMS) actuators in uGC systems. The proposed Python-based Graphical User Interface (GUI) approach leverages simple empirically-driven calculations to determine optimal gains. By interfacing with any embedded system through standard connection like Wi-Fi, the auto-tuner enables interactive, vendor-agnostic tuning while visualizing full transient response. This provides accessible, customizable auto-tuning capabilities to enhance closed-loop PID control across instrumentation and device applications at no or minimal additional hardware cost. In uGC systems, we utilize the same setup for thermal, flow, and pressure control, with additional sensor costs offset by the implementation of multiple closed loops on the same system.Precise temperature and flow control is critical in many applications, such as minimizing fluctuations in analyte retention times in uGC systems. PID control offers reliable closed-loop control for such applications, but tedious manual tuning is required for each system. The proposed auto-tuner presented in this work will greatly simplify PID tuning to improve temperature and flow rate precision in these systems. The performance is analyzed by evaluating response metrics including overshoot, rise time, and steady-state error. This thesis discusses the auto-tuning technique, PID implementation, and experimental performance analysis. Overall, this work presents a novel embedded PID automated methodology for rapid and precise thermal and flow control in uGC and other precision regulation applications. The proposed auto-tuning method provides effective tuning across a wide variety of applications such as motors, temperature and pressure control, and flow regulation systems.

Use of Slotted Waveguide Antenna Stiffened Structures (SWASS) in future commercial and military aircraft calls for the development of an airworthiness certification procedure. The first step of this procedure is to provide a computationally low-cost method for modeling waveguide antenna arrays on the scale of an aircraft skin panel using a multi-fidelity model. Weather detection radar for the Northrop Grumman X-47 unmanned air system is considered as a case study. COMSOL Multiphysics is used for creating high-fidelity waveguide models that are imported into the MATLAB Phased Array Toolbox for large-scale array calculations using a superposition method. Verification test cases show that this method is viable for relatively accurate modeling of large SWASS arrays with low computational effort. Additionally, realistic material properties for carbon fiber reinforced plastic (CFRP) are used to create a more accurate model. Optimization is performed on a 12-slot CFRP waveguide to determine the waveguide dimensions for the maximum far-field gain and separately for the maximum critical buckling load. Using the two separate optima as utopia points, a multi-objective optimization for the peak far-field gain and critical buckling load is performed, to obtain a balance between EM performance and structural strength. This optimized waveguide is then used to create a SWASS array of approximately the same size as an aircraft wing panel using the multi-fidelity modeling method that is proposed. This model is compared to a typical conventional weather radar system, and found to be well above the minimum mission requirements. / Master of Science / Antennas used in military and commercial aircraft have traditionally been designed independently from the aircraft structure. Increasingly, e↵ort has been made to integrate these processes, in order to create more efficient, dual-purpose structures. Slotted waveguide antennas, hollow rectangular tubes with slots cut in one face, are commonly used to create arrays for aircraft on-board weather radar. A type of structurally embedded antenna, slotted waveguide antenna stiffened structures (SWASS), consists of slotted waveguides that are sandwiched between two layers of a composite material. This sandwich structure can be used in place of the conventional structure used for aircraft skin, allowing the slotted waveguides to function not only as antennas, but also as part of the aircraft’s load-bearing structure. Because of the geometric complexity of the slotted waveguides, generating accurate models of the antenna performance can be difficult and requires a great deal of computational power. This thesis presents and validates a method for reducing the complexity of modeling the antenna performance of SWASS arrays. Additionally, optimizations are performed to improve both the waveguide’s performance as an antenna and as a load-bearing part of the aircraft structure. Finally, the optimized SWASS array is compared to the actual mission requirements of the Northrop Grumman X-47 unmanned aircraft, and is found to perform above the required levels.

This master thesis aimed to gain knowledge about the field of "adaptive array antenna systems for mobile satellite communication" and develop algorithms to control hardware equipment. We were able to set up and configure a beamformer to receive radio frequency (RF) signals using an array antenna. To do this we tested several development environments before settling on Python script programming using the Thonny editor. We created several plots of antenna patterns using both rectangular and polar coordinate systems, and developed Python code to generate animations and vector figures of the results. We also used different algorithms to control the pointing direction of the array antenna and examine the RF signal strength under various conditions. The results of our work can be used in future research to increase the robustness and flexibility of satellite communication and help provide redundancy against communication disruptions. To apply the findings of this master thesis more closely to a real-life application, we suggest using an field-programmable gate array (FPGA) to calculate and control beamforming, as the Raspberry Pi 4 computer used in this project is too slow for real-time processing. We also recommend using 2D-arrays instead of the 1D-array used in this project, which would allow for control of the beam lobe in both azimuth and elevation. Another suggestion is to build smaller blocks of 2D-array antennas connected with synchronized clocks into larger antenna arrays, which would result in improved performance. This was a challenging and rewarding project that provided valuable insights into a topic with many potential future applications within e.g. satellite communications, radar technology and mobile telephony.

This thesis was submitted to the faculty of Innovation, Design and Technology, IDT, at Mälardalen university in Västerås, Sweden as a partial fulfillment of the requirements to obtain the M.Sc. in computer science, specializing in embedded systems. The work presented was carried out in the months January to June in 2014 partially in Volvo Construction Equipment, Volvo CE, Eskilstuna, and partially at Mälardalen university in Västerås. Federated Resilient Embedded Systems Technology for AUTOSAR, FRESTA, is a collaborative project between Volvo and the Swedish Institute of Computer Science, SICS, that aims to make it possible to add third party applications to vehicle’s computer systems without compromising system security and robustness. The mechanism is developed by SICS for AUTOSAR, AUTomotive Open System ARchitecture, an open standardized automotive software architecture for vehicles. The following report documents the efforts to study and port the FRESTA mechanism to the Volvo CE platform, and develop a Java application to test the porting. The investigation will aspire to determine if it is feasible to introduce Java based third party applications to resource constrained embedded systems, without causing a deterioration in the predictability and security of the system. / Avhandlingen lades fram för fakulteten för innovation, design och teknik, IDT, vid Mälardalens högskola i Västerås som en del av kraven för att erhålla M.Sc. i datavetenskap med inriktning mot inbyggda system. Arbetet genomfördes under månaderna januari till juni 2014 delvis i Volvo Construction Equipment, Volvo CE, Eskilstuna, och delvis vid Mälardalens högskola i Västerås. Federated Resilient Embedded Systems Technology for AUTOSAR, FRESTA, är ett samarbetsprojekt mellan Volvo och Svenska Institutet för datavetenskap, SICS, som syftar till att göra det möjligt att lägga tredjepartsapplikationer till fordonets datorsystem utan att äventyra systemets säkerhet och robusthet. Mekanismen är utvecklat av SICS för AUTOSAR, Automotive Open System Architecture, en öppen standardiserad fordons programvaruarkitektur för fordon. Följande rapport dokumenterar arbetet med att studera Fresta mekanismen till Volvo CE-plattformen, och utveckla ett Java-program för att testa portning. Undersökningen kommer att sträva efter att avgöra om det är genomförbart att införa en Java-baserad tredje part för att resursbegränsa inbyggda system, utan att orsaka en försämring av förutsägbarhet och säkerhet i systemet.

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal.

A computação visual é uma área do conhecimento que estuda o desenvolvimento de sistemas artificiais capazes de detectar e desenvolver a percepção do meio ambiente através de informações de imagem ou dados multidimensionais. A percepção visual e a manipulação são combinadas em sistemas robóticos através de duas etapas "olhar"e depois "movimentar-se", gerando um laço de controle de feedback visual. Neste contexto, existe um interesse crescimente no uso dessas técnicas em veículos aéreos não tripulados (VANTs), também conhecidos como drones. Essas técnicas são aplicadas para posicionar o drone em modo de vôo autônomo, ou para realizar a detecção de regiões para vigilância aérea ou pontos de interesse. Os sistemas de computação visual geralmente tomam três passos em sua operação, que são: aquisição de dados em forma numérica, processamento de dados e análise de dados. A etapa de aquisição de dados é geralmente realizada por câmeras e sensores de proximidade. Após a aquisição de dados, o computador embarcado realiza o processamento de dados executando algoritmos com técnicas de medição (variáveis, índice e coeficientes), detecção (padrões, objetos ou áreas) ou monitoramento (pessoas, veículos ou animais). Os dados processados são analisados e convertidos em comandos de decisão para o controle para o sistema robótico autônomo Visando realizar a integração dos sistemas de computação visual com as diferentes plataformas de VANTs, este trabalho propõe o desenvolvimento de um framework para controle de missão e guiamento de VANTs baseado em visão computacional. O framework é responsável por gerenciar, codificar, decodificar e interpretar comandos trocados entre as controladoras de voo e os algoritmos de computação visual. Como estudo de caso, foram desenvolvidos dois algoritmos destinados à aplicação em agricultura de precisão. O primeiro algoritmo realiza o cálculo de um coeficiente de reflectância visando a aplicação auto-regulada e eficiente de agroquímicos, e o segundo realiza a identificação das linhas de plantas para realizar o guiamento dos VANTs sobre a plantação. O desempenho do framework e dos algoritmos propostos foi avaliado e comparado com o estado da arte, obtendo resultados satisfatórios na implementação no hardware embarcado. / Cumputer Vision is an area of knowledge that studies the development of artificial systems capable of detecting and developing the perception of the environment through image information or multidimensional data. Nowadays, vision systems are widely integrated into robotic systems. Visual perception and manipulation are combined in two steps "look" and then "move", generating a visual feedback control loop. In this context, there is a growing interest in using computer vision techniques in unmanned aerial vehicles (UAVs), also known as drones. These techniques are applied to position the drone in autonomous flight mode, or to perform the detection of regions for aerial surveillance or points of interest. Computer vision systems generally take three steps to the operation, which are: data acquisition in numerical form, data processing and data analysis. The data acquisition step is usually performed by cameras or proximity sensors. After data acquisition, the embedded computer performs data processing by performing algorithms with measurement techniques (variables, index and coefficients), detection (patterns, objects or area) or monitoring (people, vehicles or animals). The resulting processed data is analyzed and then converted into decision commands that serve as control inputs for the autonomous robotic system In order to integrate the visual computing systems with the different UAVs platforms, this work proposes the development of a framework for mission control and guidance of UAVs based on computer vision. The framework is responsible for managing, encoding, decoding, and interpreting commands exchanged between flight controllers and visual computing algorithms. As a case study, two algorithms were developed to provide autonomy to UAVs intended for application in precision agriculture. The first algorithm performs the calculation of a reflectance coefficient used to perform the punctual, self-regulated and efficient application of agrochemicals. The second algorithm performs the identification of crop lines to perform the guidance of the UAVs on the plantation. The performance of the proposed framework and proposed algorithms was evaluated and compared with the state of the art, obtaining satisfactory results in the implementation of embedded hardware.