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This paper addresses the schedulability problem of periodic and sporadic real-time task sets with constrained deadlines preemptively scheduled on a multiprocessor platform composed by identical processors. We assume that a global work-conserving scheduler is used and migration from one processor to another is allowed during a task lifetime. First, a general method to derive schedulability conditions for multiprocessor real-time systems will be presented. The analysis will be applied to two typical scheduling algorithms: earliest deadline first (EDF) and fixed priority (FP). Then, the derived schedulability conditions will be tightened, refining the analysis with a simple and effective technique that significantly improves the percentage of accepted task sets. The effectiveness of the proposed test is shown through an extensive set of synthetic experiments.  相似文献   
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Component-based software development established as an effective technique to cope with the increasing complexity of modern computing systems. In the context of real-time systems, the M-BROE framework has been recently proposed to efficiently support component-based development of real-time applications on multiprocessor platforms in the presence of shared resources. The framework relies on a two-stage approach where software components are first partitioned upon a virtual multiprocessor platform and are later integrated upon the physical platform by means of component interfaces that abstract from the internal details of the applications. This work presents a complete design flow for the M-BROE framework. Starting from a model of software components, a first method is proposed to partition applications to virtual processors and perform a synthesis of multiple component interfaces. Then, a second method is proposed to support the integration of the components by allocating virtual processors to physical processors. Both methods take resource sharing into account. Experimental results are also presented to evaluate the proposed methodology.  相似文献   
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EDZL scheduling analysis   总被引:2,自引:1,他引:1  
A schedulability test is derived for the global Earliest Deadline Zero Laxity (EDZL) scheduling algorithm on a platform with multiple identical processors. The test is sufficient, but not necessary, to guarantee that a system of independent sporadic tasks with arbitrary deadlines will be successfully scheduled, with no missed deadlines, by the multiprocessor EDZL algorithm. Global EDZL is known to be at least as effective as global Earliest-Deadline-First (EDF) in scheduling task sets to meet deadlines. It is shown, by testing on large numbers of pseudo-randomly generated task sets, that the combination of EDZL and the new schedulability test is able to guarantee that far more task sets meet deadlines than the combination of EDF and known EDF schedulability tests. In the second part of the paper, an improved version of the EDZL-schedulability test is presented. This new algorithm is able to efficiently exploit information on the slack values of interfering tasks, to iteratively refine the estimation of the interference a task can be subjected to. This iterative algorithm is shown to have better performance than the initial test, in terms of schedulable task sets detected.
Marko BertognaEmail:
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Preemptive scheduling often generates a significant runtime overhead that may increase task worst-case execution times up to 40%, with respect to a fully non-preemptive execution. In small embedded systems, such an extra cost results in longer and more variable response times that can significantly affect the overall energy consumption, as well as the system predictability. Limiting preemptions is often possible without jeopardizing schedulability. Although several authors addressed schedulability analysis under different forms of limited preemptive scheduling, current results exhibit two major deficiencies: (i) The maximum lengths of the non-preemptive regions for each task are still unknown under fixed priorities; (i) The exact response time analysis for tasks with fixed preemption points is too complex.  相似文献   
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Real-Time Systems - Different communication models have been historically adopted in the automotive domain for allowing concurrent tasks to coordinate, interact and synchronize on a shared memory...  相似文献   
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In scheduling hard-real-time systems, the primary objective is to meet all deadlines. We study the scheduling of such systems with the secondary objective of minimizing the duration of time for which the system locks each shared resource. We abstract out this objective into the resource hold time (rht)—the largest length of time that may elapse between the instant that a system locks a resource and the instant that it subsequently releases the resource, and study properties of the rht. We present an algorithm for computing resource hold times for every resource in a task system that is scheduled using Earliest Deadline First scheduling, with resource access arbitrated using the Stack Resource Policy. We also present and prove the correctness of algorithms for decreasing these rht’s without changing the semantics of the application or compromising application feasibility.
Sanjoy Baruah (Corresponding author)Email:
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In the last decades, ego-motion estimation or visual odometry (VO) has received a considerable amount of attention from the robotic research community, mainly due to its central importance in achieving robust localization and, as a consequence, autonomy. Different solutions have been explored, leading to a wide variety of approaches, mostly grounded on geometric methodologies and, more recently, on data-driven paradigms. To guide researchers and practitioners in choosing the best VO method, different benchmark studies have been published. However, the majority of them compare only a small subset of the most popular approaches and, usually, on specific data sets or configurations. In contrast, in this work, we aim to provide a complete and thorough study of the most popular and best-performing geometric and data-driven solutions for VO. In our investigation, we considered several scenarios and environments, comparing the estimation accuracies and the role of the hyper-parameters of the approaches selected, and analyzing the computational resources they require. Experiments and tests are performed on different data sets (both publicly available and self-collected) and two different computational boards. The experimental results show pros and cons of the tested approaches under different perspectives. The geometric simultaneous localization and mapping methods are confirmed to be the best performing, while data-driven approaches show robustness with respect to nonideal conditions present in more challenging scenarios.  相似文献   
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