949 resultados para Time constraints


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This paper focuses on the scheduling of tasks with hard and soft real-time constraints in open and dynamic real-time systems. It starts by presenting a capacity sharing and stealing (CSS) strategy that supports the coexistence of guaranteed and non-guaranteed bandwidth servers to efficiently handle soft-tasks’ overloads by making additional capacity available from two sources: (i) reclaiming unused reserved capacity when jobs complete in less than their budgeted execution time and (ii) stealing reserved capacity from inactive non-isolated servers used to schedule best-effort jobs. CSS is then combined with the concept of bandwidth inheritance to efficiently exchange reserved bandwidth among sets of inter-dependent tasks which share resources and exhibit precedence constraints, assuming no previous information on critical sections and computation times is available. The proposed Capacity Exchange Protocol (CXP) has a better performance and a lower overhead when compared against other available solutions and introduces a novel approach to integrate precedence constraints among tasks of open real-time systems.

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The rapid increase in the use of microprocessor-based systems in critical areas, where failures imply risks to human lives, to the environment or to expensive equipment, significantly increased the need for dependable systems, able to detect, tolerate and eventually correct faults. The verification and validation of such systems is frequently performed via fault injection, using various forms and techniques. However, as electronic devices get smaller and more complex, controllability and observability issues, and sometimes real time constraints, make it harder to apply most conventional fault injection techniques. This paper proposes a fault injection environment and a scalable methodology to assist the execution of real-time fault injection campaigns, providing enhanced performance and capabilities. Our proposed solutions are based on the use of common and customized on-chip debug (OCD) mechanisms, present in many modern electronic devices, with the main objective of enabling the insertion of faults in microprocessor memory elements with minimum delay and intrusiveness. Different configurations were implemented starting from basic Components Off-The-Shelf (COTS) microprocessors, equipped with real-time OCD infrastructures, to improved solutions based on modified interfaces, and dedicated OCD circuitry that enhance fault injection capabilities and performance. All methodologies and configurations were evaluated and compared concerning performance gain and silicon overhead.

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Distributed real-time systems such as automotive applications are becoming larger and more complex, thus, requiring the use of more powerful hardware and software architectures. Furthermore, those distributed applications commonly have stringent real-time constraints. This implies that such applications would gain in flexibility if they were parallelized and distributed over the system. In this paper, we consider the problem of allocating fixed-priority fork-join Parallel/Distributed real-time tasks onto distributed multi-core nodes connected through a Flexible Time Triggered Switched Ethernet network. We analyze the system requirements and present a set of formulations based on a constraint programming approach. Constraint programming allows us to express the relations between variables in the form of constraints. Our approach is guaranteed to find a feasible solution, if one exists, in contrast to other approaches based on heuristics. Furthermore, approaches based on constraint programming have shown to obtain solutions for these type of formulations in reasonable time.

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The intensity of parental investments in child care time is expected to vary across families with different norms and time-constraints. Additionally, it should also differ across countries, since the abilities of parents to harmonize family and work vary by national context. In our opinion, however, this question remains inconclusive for two main reasons: 1) only some countries have been studied from a comparative approach; 2) previous studies have not paid enough attention to the analysis of how the conditional effects of education and employment affect parental investments.In this paper we used nationally representative time-use data from Denmark, Flanders, Spain and the United Kingdom (N=4,031) to explore how employment and education predict variations in child care time. IN Britain and Spain employment has a strong negative effect on fathers’ child care, but a weaker one in Flanders and particularly in Denmark. In contrast, maternal employment has a strong negative impact in all four countries. Education increases child care time significantly only among Spanish mothers and fathers, as well as British mothers. Nonetheless, we find that college-educated mothers under similar time-constraints increase substantially their expected child care time in Britain, Flanders and Spain; for fathers we find a more mixed picture. Routine child care activities are more sensitive to both maternal and paternal employment than interactive child care activities. Finally, we observe that working a public sector job generally increases a total time allocated to parental care, controlling for several demographic and socioeconomic variables.

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PURPOSE: A new magnetic resonance imaging approach for detection of myocardial late enhancement during free-breathing was developed. METHODS AND RESULTS: For suppression of respiratory motion artifacts, a prospective navigator technology including real-time motion correction and a local navigator restore was implemented. Subject specific inversion times were defined from images with incrementally increased inversion times acquired during a single dynamic scout navigator-gated and real-time motion corrected free-breathing scan. Subsequently, MR-imaging of myocardial late enhancement was performed with navigator-gated and real-time motion corrected adjacent short axis and long axis (two, three and four chamber) views. This alternative approach was investigated in 7 patients with history of myocardial infarction 12 min after i. v. administration of 0.2 mmol/kg body weight gadolinium-DTPA. CONCLUSION: With the presented navigator-gated and real-time motion corrected sequence for MR-imaging of myocardial late enhancement data can be completely acquired during free-breathing. Time constraints of a breath-hold technique are abolished and optimized patient specific inversion time is ensured.

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The new generation of multicore processors opens new perspectives for the design of embedded systems. Multiprocessing, however, poses new challenges to the scheduling of real-time applications, in which the ever-increasing computational demands are constantly flanked by the need of meeting critical time constraints. Many research works have contributed to this field introducing new advanced scheduling algorithms. However, despite many of these works have solidly demonstrated their effectiveness, the actual support for multiprocessor real-time scheduling offered by current operating systems is still very limited. This dissertation deals with implementative aspects of real-time schedulers in modern embedded multiprocessor systems. The first contribution is represented by an open-source scheduling framework, which is capable of realizing complex multiprocessor scheduling policies, such as G-EDF, on conventional operating systems exploiting only their native scheduler from user-space. A set of experimental evaluations compare the proposed solution to other research projects that pursue the same goals by means of kernel modifications, highlighting comparable scheduling performances. The principles that underpin the operation of the framework, originally designed for symmetric multiprocessors, have been further extended first to asymmetric ones, which are subjected to major restrictions such as the lack of support for task migrations, and later to re-programmable hardware architectures (FPGAs). In the latter case, this work introduces a scheduling accelerator, which offloads most of the scheduling operations to the hardware and exhibits extremely low scheduling jitter. The realization of a portable scheduling framework presented many interesting software challenges. One of these has been represented by timekeeping. In this regard, a further contribution is represented by a novel data structure, called addressable binary heap (ABH). Such ABH, which is conceptually a pointer-based implementation of a binary heap, shows very interesting average and worst-case performances when addressing the problem of tick-less timekeeping of high-resolution timers.

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This thesis develops high performance real-time signal processing modules for direction of arrival (DOA) estimation for localization systems. It proposes highly parallel algorithms for performing subspace decomposition and polynomial rooting, which are otherwise traditionally implemented using sequential algorithms. The proposed algorithms address the emerging need for real-time localization for a wide range of applications. As the antenna array size increases, the complexity of signal processing algorithms increases, making it increasingly difficult to satisfy the real-time constraints. This thesis addresses real-time implementation by proposing parallel algorithms, that maintain considerable improvement over traditional algorithms, especially for systems with larger number of antenna array elements. Singular value decomposition (SVD) and polynomial rooting are two computationally complex steps and act as the bottleneck to achieving real-time performance. The proposed algorithms are suitable for implementation on field programmable gated arrays (FPGAs), single instruction multiple data (SIMD) hardware or application specific integrated chips (ASICs), which offer large number of processing elements that can be exploited for parallel processing. The designs proposed in this thesis are modular, easily expandable and easy to implement. Firstly, this thesis proposes a fast converging SVD algorithm. The proposed method reduces the number of iterations it takes to converge to correct singular values, thus achieving closer to real-time performance. A general algorithm and a modular system design are provided making it easy for designers to replicate and extend the design to larger matrix sizes. Moreover, the method is highly parallel, which can be exploited in various hardware platforms mentioned earlier. A fixed point implementation of proposed SVD algorithm is presented. The FPGA design is pipelined to the maximum extent to increase the maximum achievable frequency of operation. The system was developed with the objective of achieving high throughput. Various modern cores available in FPGAs were used to maximize the performance and details of these modules are presented in detail. Finally, a parallel polynomial rooting technique based on Newton’s method applicable exclusively to root-MUSIC polynomials is proposed. Unique characteristics of root-MUSIC polynomial’s complex dynamics were exploited to derive this polynomial rooting method. The technique exhibits parallelism and converges to the desired root within fixed number of iterations, making this suitable for polynomial rooting of large degree polynomials. We believe this is the first time that complex dynamics of root-MUSIC polynomial were analyzed to propose an algorithm. In all, the thesis addresses two major bottlenecks in a direction of arrival estimation system, by providing simple, high throughput, parallel algorithms.

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Linear regression is a technique widely used in digital signal processing. It consists on finding the linear function that better fits a given set of samples. This paper proposes different hardware architectures for the implementation of the linear regression method on FPGAs, specially targeting area restrictive systems. It saves area at the cost of constraining the lengths of the input signal to some fixed values. We have implemented the proposed scheme in an Automatic Modulation Classifier, meeting the hard real-time constraints this kind of systems have.

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Predicting statically the running time of programs has many applications ranging from task scheduling in parallel execution to proving the ability of a program to meet strict time constraints. A starting point in order to attack this problem is to infer the computational complexity of such programs (or fragments thereof). This is one of the reasons why the development of static analysis techniques for inferring cost-related properties of programs (usually upper and/or lower bounds of actual costs) has received considerable attention.

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A disruption predictor based on support vector machines (SVM) has been developed to be used in JET. The training process uses thousands of discharges and, therefore, high performance computing has been necessary to obtain the models. To this respect, several models have been generated with data from different JET campaigns. In addition, various kernels (mainly linear and RBF) and parameters have been tested. The main objective of this work has been the implementation of the predictor model under real-time constraints. A “C-code” software application has been developed to simulate the real-time behavior of the predictor. The application reads the signals from the JET database and simulates the real-time data processing, in particular, the specific data hold method to be developed when reading data from the JET ATM real time network. The simulator is fully configurable by means of text files to select models, signal thresholds, sampling rates, etc. Results with data between campaigns C23and C28 will be shown.

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This work describes a neural network based architecture that represents and estimates object motion in videos. This architecture addresses multiple computer vision tasks such as image segmentation, object representation or characterization, motion analysis and tracking. The use of a neural network architecture allows for the simultaneous estimation of global and local motion and the representation of deformable objects. This architecture also avoids the problem of finding corresponding features while tracking moving objects. Due to the parallel nature of neural networks, the architecture has been implemented on GPUs that allows the system to meet a set of requirements such as: time constraints management, robustness, high processing speed and re-configurability. Experiments are presented that demonstrate the validity of our architecture to solve problems of mobile agents tracking and motion analysis.

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In this project, we propose the implementation of a 3D object recognition system which will be optimized to operate under demanding time constraints. The system must be robust so that objects can be recognized properly in poor light conditions and cluttered scenes with significant levels of occlusion. An important requirement must be met: the system must exhibit a reasonable performance running on a low power consumption mobile GPU computing platform (NVIDIA Jetson TK1) so that it can be integrated in mobile robotics systems, ambient intelligence or ambient assisted living applications. The acquisition system is based on the use of color and depth (RGB-D) data streams provided by low-cost 3D sensors like Microsoft Kinect or PrimeSense Carmine. The range of algorithms and applications to be implemented and integrated will be quite broad, ranging from the acquisition, outlier removal or filtering of the input data and the segmentation or characterization of regions of interest in the scene to the very object recognition and pose estimation. Furthermore, in order to validate the proposed system, we will create a 3D object dataset. It will be composed by a set of 3D models, reconstructed from common household objects, as well as a handful of test scenes in which those objects appear. The scenes will be characterized by different levels of occlusion, diverse distances from the elements to the sensor and variations on the pose of the target objects. The creation of this dataset implies the additional development of 3D data acquisition and 3D object reconstruction applications. The resulting system has many possible applications, ranging from mobile robot navigation and semantic scene labeling to human-computer interaction (HCI) systems based on visual information.

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The real-time refinement calculus is a formal method for the systematic derivation of real-time programs from real-time specifications in a style similar to the non-real-time refinement calculi of Back and Morgan. In this paper we extend the real-time refinement calculus with procedures and provide refinement rules for refining real-time specifications to procedure calls. A real-time specification can include constraints on, not only what outputs are produced, but also when they are produced. The derived programs can also include time constraints oil when certain points in the program must be reached; these are expressed in the form of deadline commands. Such programs are machine independent. An important consequence of the approach taken is that, not only are the specifications machine independent, but the whole refinement process is machine independent. To implement the machine independent code on a target machine one has a separate task of showing that the compiled machine code will reach all its deadlines before they expire. For real-time programs, externally observable input and output variables are essential. These differ from local variables in that their values are observable over the duration of the execution of the program. Hence procedures require input and output parameter mechanisms that are references to the actual parameters so that changes to external inputs are observable within the procedure and changes to output parameters are externally observable. In addition, we allow value and result parameters. These may be auxiliary parameters, which are used for reasoning about the correctness of real-time programs as well as in the expression of timing deadlines, but do not lead to any code being generated for them by a compiler. (c) 2006 Elsevier B.V. All rights reserved.

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Business environments have become exceedingly dynamic and competitive in recent times. This dynamism is manifested in the form of changing process requirements and time constraints. Workflow technology is currently one of the most promising fields of research in business process automation. However, workflow systems to date do not provide the flexibility necessary to support the dynamic nature of business processes. In this paper we primarily discuss the issues and challenges related to managing change and time in workflows representing dynamic business processes. We also present an analysis of workflow modifications and provide feasibility considerations for the automation of this process.

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Modern distributed control systems comprise of a set of processors which are interconnected using a suitable communication network. For use in real-time control environments, such systems must be deterministic and generate specified responses within critical timing constraints. Also, they should be sufficiently robust to survive predictable events such as communication or processor faults. This thesis considers the problem of coordinating and synchronizing a distributed real-time control system under normal and abnormal conditions. Distributed control systems need to periodically coordinate the actions of several autonomous sites. Often the type of coordination required is the all or nothing property of an atomic action. Atomic commit protocols have been used to achieve this atomicity in distributed database systems which are not subject to deadlines. This thesis addresses the problem of applying time constraints to atomic commit protocols so that decisions can be made within a deadline. A modified protocol is proposed which is suitable for real-time applications. The thesis also addresses the problem of ensuring that atomicity is provided even if processor or communication failures occur. Previous work has considered the design of atomic commit protocols for use in non time critical distributed database systems. However, in a distributed real-time control system a fault must not allow stringent timing constraints to be violated. This thesis proposes commit protocols using synchronous communications which can be made resilient to a single processor or communication failure and still satisfy deadlines. Previous formal models used to design commit protocols have had adequate state coverability but have omitted timing properties. They also assumed that sites communicated asynchronously and omitted the communications from the model. Timed Petri nets are used in this thesis to specify and design the proposed protocols which are analysed for consistency and timeliness. Also the communication system is mcxielled within the Petri net specifications so that communication failures can be included in the analysis. Analysis of the Timed Petri net and the associated reachability tree is used to show the proposed protocols always terminate consistently and satisfy timing constraints. Finally the applications of this work are described. Two different types of applications are considered, real-time databases and real-time control systems. It is shown that it may be advantageous to use synchronous communications in distributed database systems, especially if predictable response times are required. Emphasis is given to the application of the developed commit protocols to real-time control systems. Using the same analysis techniques as those used for the design of the protocols it can be shown that the overall system performs as expected both functionally and temporally.