Dependable Embedded Systems

This Open Access book introduces readers to many new techniques for enhancing and optimizing reliability in embedded systems, which have emerged particularly within the last five years. This book introduces the most prominent reliability concerns from today’s points of view and roughly recapitulates the progress in the community so far. Unlike other books that focus on a single abstraction level such circuit level or system level alone, the focus of this book is to deal with the different reliability challenges across different levels starting from the physical level all the way to the system level (cross-layer approaches). The book aims at demonstrating how new hardware/software co-design solution can be proposed to ef-fectively mitigate reliability degradation such as transistor aging, processor variation, temperature effects, soft errors, etc. Provides readers with latest insights into novel, cross-layer methods and models with respect to dependability of embedded systems; Describes cross-layer approaches that can leverage reliability through techniques that are pro-actively designed with respect to techniques at other layers; Explains run-time adaptation and concepts/means of self-organization, in order to achieve error resiliency in complex, future many core systems

A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications

Particle swarm optimization (PSO) is a heuristic global optimization method, proposed originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used optimization techniques. This survey presented a comprehensive investigation of PSO. On one hand, we provided advances with PSO, including its modifications (including quantum-behaved PSO, bare-bones PSO, chaotic PSO, and fuzzy PSO), population topology (as fully connected, von Neumann, ring, star, random, etc.), hybridization (with genetic algorithm, simulated annealing, Tabu search, artificial immune system, ant colony algorithm, artificial bee colony, differential evolution, harmonic search, and biogeography-based optimization), extensions (to multiobjective, constrained, discrete, and binary optimization), theoretical analysis (parameter selection and tuning, and convergence analysis), and parallel implementation (in multicore, multiprocessor, GPU, and cloud computing forms). On the other hand, we offered a survey on applications of PSO to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research, mechanical engineering, fuel and energy, medicine, chemistry, and biology. It is hoped that this survey would be beneficial for the researchers studying PSO algorithms

HIERARCHICAL MAPPING TECHNIQUES FOR SIGNAL PROCESSING SYSTEMS ON PARALLEL PLATFORMS

Dataflow models are widely used for expressing the functionality of digital signal processing (DSP) applications due to their useful features, such as providing formal mechanisms for description of application functionality, imposing minimal data-dependency constraints in specifications, and exposing task and data level parallelism effectively. Due to the increased complexity of dynamics in modern DSP applications, dataflow-based design methodologies require significant enhancements in modeling and scheduling techniques to provide for efficient and flexible handling of dynamic behavior. To address this problem, in this thesis, we propose an innovative framework for mode- and dynamic-parameter-based modeling and scheduling. We apply, in a systematically integrated way, the structured mode-based dataflow modeling capability of dynamic behavior together with the features of dynamic parameter reconfiguration and quasi-static scheduling. Moreover, in our proposed framework, we present a new design method called parameterized multidimensional design hierarchy mapping (PMDHM), which is targeted to the flexible, multi-level reconfigurability, and intensive real-time processing requirements of emerging dynamic DSP systems. The proposed approach allows designers to systematically represent and transform multi-level specifications of signal processing applications from a common, dataflow-based application-level model. In addition, we propose a new technique for mapping optimization that helps designers derive efficient, platform-specific parameters for application-to-architecture mapping. These parameters help to maximize system performance on state-of-the-art parallel platforms for embedded signal processing. To further enhance the scalability of our design representations and implementation techniques, we present a formal method for analysis and mapping of parameterized DSP flowgraph structures, called topological patterns, into efficient implementations. The approach handles an important class of parameterized schedule structures in a form that is intuitive for representation and efficient for implementation. We demonstrate our methods with case studies in the fields of wireless communication and computer vision. Experimental results from these case studies show that our approaches can be used to derive optimized implementations on parallel platforms, and enhance trade-off analysis during design space exploration. Furthermore, their basis in formal modeling and analysis techniques promotes the applicability of our proposed approaches to diverse signal processing applications and architectures

A novel control architecture based on behavior trees for an omni-directional mobile robot

Robotic systems are increasingly present in dynamic environments. This paper proposes a hierarchical control structure wherein a behavior tree (BT) is used to improve the flexibility and adaptability of an omni-directional mobile robot for point stabilization. Flexibility and adaptability are crucial at each level of the sense–plan–act loop to implement robust and effective robotic solutions in dynamic environments. The proposed BT combines high-level decision making and continuous execution monitoring while applying non-linear model predictive control (NMPC) for the point stabilization of an omni-directional mobile robot. The proposed control architecture can guide the mobile robot to any configuration within the workspace while satisfying state constraints (e.g., obstacle avoidance) and input constraints (e.g., motor limits). The effectiveness of the controller was validated through a set of realistic simulation scenarios and experiments in a real environment, where an industrial omni-directional mobile robot performed a point stabilization task with obstacle avoidance in a workspace.This work was financed by national funds from the FCT (Foundation for Science and Technology), I.P., through IDMEC under LAETA, project UIDB\50022\2020. The work of Rodrigo Bernardo was supported by the PhD Scholarship BD\6841\2020 from the FCT. This work indirectly received funding from the European Union’s Horizon 2020 programme under StandICT.eu 2026 (Grant Agreement No. 101091933).info:eu-repo/semantics/publishedVersio

A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs

Online scheduling for real-time multitasking on reconfigurable hardware devices

Nowadays the ever increasing algorithmic complexity of embedded applications requires the designers to turn towards heterogeneous and highly integrated systems denoted as SoC (System-on-a-Chip). These architectures may embed CPU-based processors, dedicated datapaths as well as recon gurable units. However, embedded SoCs are submitted to stringent requirements in terms of speed, size, cost, power consumption, throughput, etc. Therefore, new computing paradigms are required to ful l the constraints of the applications and the requirements of the architecture. Recon gurable Computing is a promising paradigm that provides probably the best trade-o between these requirements and constraints. Dynamically recon gurable architectures are their key enabling technology. They enable the hardware to adapt to the application at runtime. However, these architectures raise new challenges in SoC design. For example, on one hand, designing a system that takes advantage of dynamic recon guration is still very time consuming because of the lack of design methodologies and tools. On the other hand, scheduling hardware tasks di ers from classical software tasks scheduling on microprocessor or multiprocessors systems, as it bears a further complicated placement problem. This thesis deals with the problem of scheduling online real-time hardware tasks on Dynamically Recon gurable Hardware Devices (DRHWs). The problem is addressed from two angles : (i) Investigating novel algorithms for online real-time scheduling/placement on DRHWs. (ii) Scheduling/Placement algorithms library for RTOS-driven Design Space Exploration (DSE). Regarding the first point, the thesis proposes two main runtime-aware scheduling and placement techniques and assesses their suitability for online real-time scenarios. The first technique discusses the impact of synthesizing, at design time, several shapes and/or sizes per hardware task (denoted as multi-shape task), in order to ease the online scheduling process. The second technique combines a looking-ahead scheduling approach with a slots-based recon gurable areas management that relies on a 1D placement. The results show that in both techniques, the scheduling and placement quality is improved without signi cantly increasing the algorithm time complexity. Regarding the second point, in the process of designing SoCs embedding recon gurable parts, new design paradigms tend to explore and validate as early as possible, at system level, the architectural design space. Therefore, the RTOS (Real-Time Operating System) services that manage the recon gurable parts of the SoC can be re fined. In such a context, gathering numerous hardware tasks scheduling and placement algorithms of various complexity vs performance trade-o s in a kind of library is required. In this thesis, proposed algorithms in addition to some existing ones are purposely implemented in C++ language, in order to insure the compatibility with any C++/SystemC based SoC design methodology.EThOS - Electronic Theses Online ServiceGBUnited Kingdo