949 resultados para Embedded processor
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Thesis submitted in the fulfilment of the requirements for the Degree of Master in Electronic and Telecomunications Engineering
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações
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Comunication in Internationa Conference with Peer Review First International Congress on Cardiovasular Technologies - CARDIOTECHNIX, Vilamoura, Portugal, 2013
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Research on the problem of feature selection for clustering continues to develop. This is a challenging task, mainly due to the absence of class labels to guide the search for relevant features. Categorical feature selection for clustering has rarely been addressed in the literature, with most of the proposed approaches having focused on numerical data. In this work, we propose an approach to simultaneously cluster categorical data and select a subset of relevant features. Our approach is based on a modification of a finite mixture model (of multinomial distributions), where a set of latent variables indicate the relevance of each feature. To estimate the model parameters, we implement a variant of the expectation-maximization algorithm that simultaneously selects the subset of relevant features, using a minimum message length criterion. The proposed approach compares favourably with two baseline methods: a filter based on an entropy measure and a wrapper based on mutual information. The results obtained on synthetic data illustrate the ability of the proposed expectation-maximization method to recover ground truth. An application to real data, referred to official statistics, shows its usefulness.
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In this paper we survey the most relevant results for the prioritybased schedulability analysis of real-time tasks, both for the fixed and dynamic priority assignment schemes. We give emphasis to the worst-case response time analysis in non-preemptive contexts, which is fundamental for the communication schedulability analysis. We define an architecture to support priority-based scheduling of messages at the application process level of a specific fieldbus communication network, the PROFIBUS. The proposed architecture improves the worst-case messages’ response time, overcoming the limitation of the first-come-first-served (FCFS) PROFIBUS queue implementations.
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Aerodynamic drag is known to be one of the factors contributing more to increased aircraft fuel consumption. The primary source of skin friction drag during flight is the boundary layer separation. This is the layer of air moving smoothly in the immediate vicinity of the aircraft. In this paper we discuss a cyber-physical system approach able of performing an efficient suppression of the turbulent flow by using a dense sensing deployment to detect the low pressure region and a similarly dense deployment of actuators to manage the turbulent flow. With this concept, only the actuators in the vicinity of a separation layer are activated, minimizing power consumption and also the induced drag.
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Real-time embedded applications require to process large amounts of data within small time windows. Parallelize and distribute workloads adaptively is suitable solution for computational demanding applications. The purpose of the Parallel Real-Time Framework for distributed adaptive embedded systems is to guarantee local and distributed processing of real-time applications. This work identifies some promising research directions for parallel/distributed real-time embedded applications.
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A large part of power dissipation in a system is generated by I/O devices. Increasingly these devices provide power saving mechanisms to inter alia enhance battery life. While I/O device scheduling has been studied in the past for realtime systems, the use of energy resources by these scheduling algorithms may be improved. These approaches are crafted considering a huge overhead of device transition. The technology enhancement has allowed the hardware vendors to reduce the device transition overhead and energy consumption. We propose an intra-task device scheduling algorithm for real time systems that allows to shut-down devices while ensuring the system schedulability. Our results show an energy gain of up to 90% in the best case when compared to the state-of-the-art.
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Embedded real-time applications increasingly present high computation requirements, which need to be completed within specific deadlines, but that present highly variable patterns, depending on the set of data available in a determined instant. The current trend to provide parallel processing in the embedded domain allows providing higher processing power; however, it does not address the variability in the processing pattern. Dimensioning each device for its worst-case scenario implies lower average utilization, and increased available, but unusable, processing in the overall system. A solution for this problem is to extend the parallel execution of the applications, allowing networked nodes to distribute the workload, on peak situations, to neighbour nodes. In this context, this report proposes a framework to develop parallel and distributed real-time embedded applications, transparently using OpenMP and Message Passing Interface (MPI), within a programming model based on OpenMP. The technical report also devises an integrated timing model, which enables the structured reasoning on the timing behaviour of these hybrid architectures.
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Despite the steady increase in experimental deployments, most of research work on WSNs has focused only on communication protocols and algorithms, with a clear lack of effective, feasible and usable system architectures, integrated in a modular platform able to address both functional and non–functional requirements. In this paper, we outline EMMON [1], a full WSN-based system architecture for large–scale, dense and real–time embedded monitoring [3] applications. EMMON provides a hierarchical communication architecture together with integrated middleware and command and control software. Then, EM-Set, the EMMON engineering toolset will be presented. EM-Set includes a network deployment planning, worst–case analysis and dimensioning, protocol simulation and automatic remote programming and hardware testing tools. This toolset was crucial for the development of EMMON which was designed to use standard commercially available technologies, while maintaining as much flexibility as possible to meet specific applications requirements. Finally, the EMMON architecture has been validated through extensive simulation and experimental evaluation, including a 300+ nodes testbed.
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The recent trends of chip architectures with higher number of heterogeneous cores, and non-uniform memory/non-coherent caches, brings renewed attention to the use of Software Transactional Memory (STM) as a fundamental building block for developing parallel applications. Nevertheless, although STM promises to ease concurrent and parallel software development, it relies on the possibility of aborting conflicting transactions to maintain data consistency, which impacts on the responsiveness and timing guarantees required by embedded real-time systems. In these systems, contention delays must be (efficiently) limited so that the response times of tasks executing transactions are upper-bounded and task sets can be feasibly scheduled. In this paper we assess the use of STM in the development of embedded real-time software, defending that the amount of contention can be reduced if read-only transactions access recent consistent data snapshots, progressing in a wait-free manner. We show how the required number of versions of a shared object can be calculated for a set of tasks. We also outline an algorithm to manage conflicts between update transactions that prevents starvation.
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Preemptions account for a non-negligible overhead during system execution. There has been substantial amount of research on estimating the delay incurred due to the loss of working sets in the processor state (caches, registers, TLBs) and some on avoiding preemptions, or limiting the preemption cost. We present an algorithm to reduce preemptions by further delaying the start of execution of high priority tasks in fixed priority scheduling. Our approaches take advantage of the floating non-preemptive regions model and exploit the fact that, during the schedule, the relative task phasing will differ from the worst-case scenario in terms of admissible preemption deferral. Furthermore, approximations to reduce the complexity of the proposed approach are presented. Substantial set of experiments demonstrate that the approach and approximations improve over existing work, in particular for the case of high utilisation systems, where savings of up to 22% on the number of preemption are attained.
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Consider the problem of scheduling a set of sporadic tasks on a multiprocessor system to meet deadlines using a task-splitting scheduling algorithm. Task-splitting (also called semi-partitioning) scheduling algorithms assign most tasks to just one processor but a few tasks are assigned to two or more processors, and they are dispatched in a way that ensures that a task never executes on two or more processors simultaneously. A particular type of task-splitting algorithms, called slot-based task-splitting dispatching, is of particular interest because of its ability to schedule tasks with high processor utilizations. Unfortunately, no slot-based task-splitting algorithm has been implemented in a real operating system so far. In this paper we discuss and propose some modifications to the slot-based task-splitting algorithm driven by implementation concerns, and we report the first implementation of this family of algorithms in a real operating system running Linux kernel version 2.6.34. We have also conducted an extensive range of experiments on a 4-core multicore desktop PC running task-sets with utilizations of up to 88%. The results show that the behavior of our implementation is in line with the theoretical framework behind it.
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Consider the problem of scheduling a set of sporadic tasks on a multiprocessor system to meet deadlines using a tasksplitting scheduling algorithm. Task-splitting (also called semipartitioning) scheduling algorithms assign most tasks to just one processor but a few tasks are assigned to two or more processors, and they are dispatched in a way that ensures that a task never executes on two or more processors simultaneously. A certain type of task-splitting algorithms, called slot-based task-splitting, is of particular interest because of its ability to schedule tasks at high processor utilizations. We present a new schedulability analysis for slot-based task-splitting scheduling algorithms that takes the overhead into account and also a new task assignment algorithm.
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Wireless sensor networks (WSNs) have attracted growing interest in the last decade as an infrastructure to support a diversity of ubiquitous computing and cyber-physical systems. However, most research work has focused on protocols or on specific applications. As a result, there remains a clear lack of effective and usable WSN system architectures that address both functional and non-functional requirements in an integrated fashion. This poster outlines the EMMON system architecture for large-scale, dense, real-time embedded monitoring. It provides a hierarchical communication architecture together with integrated middleware and command and control software. It has been designed to maintain as much as flexibility as possible while meeting specific applications requirements. EMMON has been validated through extensive analytical, simulation and experimental evaluations, including through a 300+ nodes test-bed the largest single-site WSN test-bed in Europe.