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Modern embedded systems are evolving in the direction of increased adaptivity and complexity. It is extremely important for a system with limited resource to be adaptive in order to maximize its efficiency of resource usage while guaranteeing a high level of fault tolerance and QoS. This report aims at exploring such a kind of system, i.e. Adaptive Embedded System (AES), which is featured by dynamic reconfiguration at runtime. Based on the investigation and analysis of a variety of case studies related with AES, we proposed the conceptual view and overall architecture of an AES by highlighting its predominant characteristics. We also made an incomplete but detailed summary of the most popular techniques that can be used to realize adaptivity. Those techniques are categorized into dynamic CPU/network resource re-allocation and adaptive fault tolerance. A majority of adaptive applications resort to one or more of those techniques. Besides, there is a separate discussion on dynamic reconfiguration and mode switch for AES. Finally, we classify adaptivity into different modeling problems at a higher abstraction level and build UPPAAL models for two different AESs, a smart phone and an object-tracking robot. Our UPPAAL models provide clear demonstration on how a typical AES works.

Speech recognition has been an important area of research during the past decades. The usage of automatic speech recognition systems is rapidly increasing among different areas, such as mobile telephony, automotive, healthcare, robotics and more. However, despite the existence of many speech recognition systems, most of them use platform specific and non-publicly available software. Nevertheless, it is possible to develop speech recognition systems using already existing open source technology. The aim of this master's thesis is to develop an interactive and speaker independent speech recognition system. The system shall be able to identify predetermined keywords from incoming live speech and in response, play audio files with related information. Moreover, the system shall be able to provide a response even if no keyword was identified. For this project, the system was implemented using PocketSphinx, a speech recognition library, part of the open source Sphinx technology by the Carnegie Mellon University. During the implementation of this project, the automation of different steps of the process, was a key factor for a successful completion. This automation consisted on the development of different tools for the creation of the language model and the dictionary, two important components of the system. Similarly, the audio files to be played after identifying a keyword, as well as the evaluation of the system's performance, were fully automated. The tests run show encouraging results and demonstrate that the system is a feasible solution that could be implemented and tested in a real embedded application. Despite the good results, possible improvements can be implemented, such as the creation of a different phonetic dictionary to support different languages.

The number of electronic control units in heavy-duty vehicles has grown dramatically overthe last few decades. This has led to the use of communication buses to reduce the complexityand weight of the networks. There are reasons to believe that the de facto standardcommunication interface in the automotive industry, the Controller Area Network, is obsoletein some areas. Hence an evaluation of available communication interfaces is needed.This study focuses on lower levels of the Open Systems Interconnect (osi) model. Initially atheoretical study is presented in order to give an overview of automotive embedded systemsin general and different communication interfaces in particular. Ethernet and FlexRay areidentified as two interfaces of interest for future use in Scanias vehicles. The former is new inautomotive applications but is believed to become popular over the years to come. A possibleuse of this interface could be as a backbone to take the load off other interfaces. The use ofFlexRay in Scanias vehicles is limited because of the modular system used and the staticscheduling needed. It could however be used between mandatory ecus where the nodes andthe messages are all known beforehand.The report also contains the result from emission measurements on a number of interfacesperformed using a stripline antenna in a shielded enclosure. Strong conclusions can not bedrawn since it’s hard to tell what the transceivers, circuit boards and interfaces contributedto in the spectra with the method used. The FlexRay hardware is worse than for the otherinterfaces. Similarities can be seen between low-speed and high-speed can but it could becharacteristics of the transceivers used rather than the interface itself.

In this dissertation, we investigate the capacity and performance of wireless networks with an emphasis on multicast traffic. The defining characteristic of a multicast network is a network where a number of different destinations all require the information generated by a single source. The models that we explore differ in the nature of the nodes from all-mobile case where all nodes are mobile to hybrid case where some nodes are mobile and some are static. We investigate different performance measure for these wireless multicast networks: upper bounds, capacity scaling laws, and achievable rates. The understanding of these measures for such networks helps in the development of efficient algorithms for operating these networks. In addition, we study the practical realization of algorithms for real-time streaming of rich multimedia content in the context of mobile wireless networks for embedded and cyberphysical systems. Our initial work is in the context of unicast and multiple unicast systems over an autonomous aerial vehicle (AAV) network. Bandwidth requirements and stringent delay constraints of real-time video streaming, paired with limitations on computational complexity and power consumptions imposed by the underlying implementation platform, make cross-layer and cross-domain co-design approaches a necessity. In this dissertation, we propose a novel, low-complexity rate-distortion optimized (RDO) protocol specifically targeted at video streaming over mobile embedded networks. First, we test the performance of our RDO algorithm on simulation models developed for aerial mobility of multiple wirelessly communicating AAVs. Second, we test the performance of our RDO algorithm and other proposed adaptive algorithms on a real network of AAVs and present a comparative study between these different algorithms. Note that generalizing these algorithms to multicast settings is relatively straightforward and thus is not highlighted to a great degree in this thesis. / text

Abstract—This paper proposes a new approach for the optimal integrated control and real-time scheduling of control tasks. First, the problem of the optimal integrated control and nonpreemptive off-line scheduling of control tasks in the sense of the H2 performance criterion is addressed. It is shown that this problem may be decomposed into two sub-problems. The first sub-problem aims at finding the optimal non-preemptive off-line schedule, and may be solved using the branch and bound method. The second sub-problem uses the lifting technique to determine the optimal control gains, based on the solution of the first sub-problem. Second, an efficient on-line scheduling algorithm is proposed. This algorithm, called Reactive Pointer Placement (RPP) scheduling algorithm, uses the plant state information to dispatch the computational resources in a way that improves control performance. Control performance improvements as well as stability guarantees are formally proven. Finally, simulations as well as experimental results are presented in order to illustrate the effectiveness of the proposed approach.

Wireless sensor network technology has now been widely adopted. In many applications, distributed sensor nodes collect data at different locations and the location information of each node is required. The Global Positioning System is commonly used to identify the location of the nodes in such networks. Although GPS localization has consistent long-term accuracy, it is limited by the inherent dependency on a direct line of sight to 4 or more external satellites. The increasing demand for an embedded system providing reliable navigation solutions regardless of its operational environment has motivated investigations into the use of integrated systems that combine inertial sensors with GPS receivers. This research proposes a hardware architecture for location-based wireless sensor networks. In this architecture, each sensor node consists of a GPS receiver, a reduced set of low cost micro-electro-mechanical-system-based INS and a wireless transceiver. Sensor nodes in WSN are often equipped with irreplaceable batteries, which makes the power consumption crucial. To reduce the energy consumption, a microcontroller is used to control the power supply. Besides, a motion detection scheme is proposed by taking advantage of the ultra low-power wake-up function of the microcontroller. A low-power featured digital signal processor is used to accomplish the navigation computation using the Kalman filter for GPS/INS data fusion. Non-Holonomic Constraints derived velocity updates are applied to reduce the position errors. Field tests are conducted to verify the real-time performance of the proposed system with a positioning update rate of 20 Hz. The first test shows that the 2D INS/GPS integration can maintain the average system position error within 5 meters during a 60-second GPS outage. The second test used low cost inertial sensors. The average position error was 10.17 meters during a 20-second outage. The largest RMS value of position errors among these outages was within 14.5 meters. Furthermore, additional accuracy improvements of approximately 1.4 meters were achieved by utilizing NHC during GPS outages. The third test shows that the average error during a 30-second outage is approximately 20.6 meters for the on-foot scenario and 26.7 meters for the in-vehicle scenario. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2012-01-13 14:46:45.44

The design of a framework to control multiple semi-autonomous mobile robots is presented. The goals are to create a flexible framework that allows easy task reconfiguration for a fleet of mobile robots, and to provide a means of off-loading computationally intensive tasks to a central server. Four major components are specified: controllable devices, application servers, an application directory, and a mobile management system. Remote firmware upgrades via the mobile management system are achieved with the remotely managed operating system framework or RMOS. A prototype was created using field programmable gate arrays and system on a programmable chip technology from Altera. It was built with the application of selective herbicide spraying in mind. Although the prototype was a successful implementation of the designed framework, selective herbicide application was not implemented. A broad-leaf weed detection algorithm using Boltzmann machines was investigated. Its performance was good, but similar to that obtained by a statistical analysis of the input images of a lawn.

Recently, we have seen an increase in the deployment of safety critical embedded systems in rapidly changing environments, as well as requirement for on-site customizations and rapid adaptation. To address the extended range of requirements, adaptation mechanism are added to the systems to handle large number of situations appropriately. Although necessary, adaptations can cause inconsistent and unstable configurations that must be prevented for the embedded system to remain dependable and safe. Therefore, verifying the behavior of adaptive embedded systems during the design phase of the production process is highly desirable. A hard real time embedded system and its environment can be modeled using timed automata. Such model can describe the system at various levels of abstraction. In this thesis, we model the adaptive responses of a system in terms of tasks that are executed to handle changes in the environmental or internal parameters. Schedulability, a property that all tasks complete execution within their respective deadlines, is a key element in designing hard real-time embedded systems. A system that is unschedulable immediately compromises safety and hard real-time requirements and can cause fatal failure. Given specifications of all tasks in the system, we can model the system, an abstraction of the environment, and adaptive strategies to investigate whether the system retains safety properties, including schedulability, regardless of the changes in the environment and adaptations to those changes.

In safety-critical real-time embedded systems, correctness is of primary concern, as even small transient errors may lead to catastrophic consequences. Due to the limitations of well-established methods such as verification and testing, recently runtime verification has emerged as a complementary approach, where a monitor inspects the system to evaluate the specifications at run time. The goal of runtime verification is to monitor the behavior of a system to check its conformance to a set of desirable logical properties. The literature of runtime verification mostly focuses on event-triggered solutions, where a monitor is invoked when a significant event occurs (e.g., change in the value of some variable used by the properties). At invocation, the monitor evaluates the set of properties of the system that are affected by the occurrence of the event. This type of monitor invocation has two main runtime characteristics: (1) jittery runtime overhead, and (2) unpredictable monitor invocations. These characteristics result in transient overload situations and over-provisioning of resources in real-time embedded systems and hence, may result in catastrophic outcomes in safety-critical systems. To circumvent the aforementioned defects in runtime verification, this dissertation introduces a novel time-triggered monitoring approach, where the monitor takes samples from the system with a constant frequency, in order to analyze the system's health. We describe the formal semantics of time-triggered monitoring and discuss how to optimize the sampling period using minimum auxiliary memory and path prediction techniques. Experiments on real-time embedded systems show that our approach introduces bounded overhead, predictable monitoring, less over-provisioning, and effectively reduces the involvement of the monitor at run time by using negligible auxiliary memory. We further advance our time-triggered monitor to component-based multi-core embedded systems by establishing an optimization technique that provides the invocation frequency of the monitors and the mapping of components to cores to minimize monitoring overhead. Lastly, we present RiTHM, a fully automated and open source tool which provides time-triggered runtime verification specifically for real-time embedded systems developed in C.