The Design and Development of a Multi-Disciplinary Project in Embedded Systems Design

As has been noted over the past ten years, “The wall between computer science and electrical engineering has kept the potential of embedded systems at bay. It is time to build a new scientific foundation with embedded systems design as the cornerstone, which will ensure a systematic and even-handed integration of the two fields.”[1] In Baylor University’s School of Engineering & Computer Science, the Embedded Systems course in the Department of Computer Science, and the Embedded Systems Design course in the Department of Electrical and Computer Engineering have been offered independent of each other in the recent past. In the past year, however, this is beginning to change, with plans developing to combine the project portion of the two courses into one multi-disciplinary group project. This paper will document the two courses – scope and sequence, as well as emphasis, equipment used, and delivery style – highlighting the need for a new and innovative approach at the systematic integration of software and hardware in the design and development of a mutli-disciplinary group project. The beta test of this group project is occurring in the fall 2017 semester, with full first-time full-scale deployment during the spring 2018 semester. The results of this beta test will be discussed, and the lessons learned and planned modifications to the course will be considered.Cockrell School of Engineerin

Actual Test Coverage for Embedded Systems

Testing embedded systems is inherently incomplete; no test suite will ever be able to test all possible usage scenarios. Therefore, in the past decades many coverage measures have been developed. These measures denote the portion of a system that is tested, that way providing a quality criterion for test suites. Formulating coverage criteria is not an easy task. The measures provided in the literature are consequently almost all very trivial and syntax-dependent. Well-known examples are statement and path coverage in white-box testing, and state and transition coverage in black-box testing. The complexity of designing coverage measures for embedded systems is contained in the highly dynamic behaviour of such systems, which is state-dependent and subject to many interleavings. In this talk we introduce a framework on actual test coverage. This measure denotes the number of faults actually shown present or absent. Our framework contains a method to evaluate the actual coverage of a given set of test suite executions after testing has taken place, providing a means to express the quality of a testing process. It also contains a method to predict the actual coverage a certain number of executions will yield, providing a means to select the best test suite. Both the evaluation afterwards and the prediction in advance are quite efficient, making it feasible to implement the theory in a tool and use it in a practical context

A Survey of Techniques For Improving Energy Efficiency in Embedded Computing Systems

Recent technological advances have greatly improved the performance and features of embedded systems. With the number of just mobile devices now reaching nearly equal to the population of earth, embedded systems have truly become ubiquitous. These trends, however, have also made the task of managing their power consumption extremely challenging. In recent years, several techniques have been proposed to address this issue. In this paper, we survey the techniques for managing power consumption of embedded systems. We discuss the need of power management and provide a classification of the techniques on several important parameters to highlight their similarities and differences. This paper is intended to help the researchers and application-developers in gaining insights into the working of power management techniques and designing even more efficient high-performance embedded systems of tomorrow

Sensitivity-based multistep MPC for embedded systems

In model predictive control (MPC), an optimization problem is solved every sampling instant to determine an optimal control for a physical system. We aim to accelerate this procedure for fast systems applications and address the challenge of implementing the resulting MPC scheme on an embedded system with limited computing power. We present the sensitivity-based multistep MPC, a strategy which considerably reduces the computing requirements in terms of floating point operations (FLOPs), compared to a standard MPC formulation, while fulfilling closed- loop performance expectations. We illustrate by applying the method to a DC-DC converter model and show how a designer can optimally trade off closed-loop performance considerations with computing requirements in order to fit the controller into a resource-constrained embedded system