Recently, there have been several promising techniques developed for schedulability analysis and response time analysis for multiprocessor systems based on over-approximation. This paper contains two contributions. First, to improve the analysis precision, we apply Baruah's window analysis framework [6] to response time analysis for sporadic tasks on multiprocessor systems where the deadlines of tasks are within their periods. The crucial observation is that for global fixed priority scheduling, a response time bound of each task can be efficiently estimated by fixed-point computation without enumerating all the busy window sizes as in [6] for schedulability analysis. The technique is proven to dominate theoretically state-of-the-art techniques for response time analysis for multiprocessor systems. Our experiments also show that the technique results in significant performance improvement compared with several existing techniques for multiprocessor schedulability analysis. As the second main contribution of this paper, we extend the proposed technique to task systems with arbitrary deadlines, allowing tasks to have deadlines beyond the end of their periods. This is a non-trivial extension even for single-processor systems. To our best knowledge, this is the first work for multiprocessor systems in this setting, which involves sophisticated techniques for the characterization and computation of response time bounds.

Abstract-Models for real-time systems have to balance the inherently contradicting goals of expressiveness and analysis efficiency. Current task models with tractable feasibility tests have limited expressiveness, restricting their ability to model many systems accurately. In particular, they are all recurrent, preventing the modeling of structures like mode switches, local loops, etc.In this paper, we advance the state-of-the-art with a model that is free from these constraints. Our proposed task model is based on arbitrary directed graphs (digraphs) for job releases. We show that the feasibility problem on preemptive uniprocessors for our model remains tractable. This even holds in the case of task systems with arbitrary deadlines.

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Abstract-An increasing trend in embedded system design is to integrate components with different levels of criticality into a shared hardware platform for better cost and power efficiency. Such mixed-criticality systems are subject to certifications at different levels of rigorousness, for validating the correctness of different subsystems on various confidence levels. The realtime scheduling of certifiable mixed-criticality systems has been recognized to be a challenging problem, where using traditional scheduling techniques may result in unacceptable resource waste. In this paper we present an algorithm called PLRS to schedule certifiable mixed-criticality sporadic tasks systems. PLRS uses fixed-job-priority scheduling, and assigns job priorities by exploring and balancing the asymmetric effects between the workload on different criticality levels. Comparing with the state-of-the-art algorithm by Li and Baruah for such systems, which we refer to as LB, PLRS is both more effective and more efficient: (i) The schedulability test of PLRS not only theoretically dominates, but also on average significantly outperforms LB's. (ii) The run-time complexity of PLRS is polynomial (quadratic in the number of tasks), which is much more efficient than the pseudo-polynomial run-time complexity of LB.

There is a clinical need for new bronchodilator drugs in asthma, because more than half of asthmatic patients do not receive adequate control with current available treatments. We report that inhibition of metallothionein-2 protein expression in lung tissues causes the increase of pulmonary resistance. Conversely, metallothionein-2 protein is more effective than β-agonists in reducing pulmonary resistance in rodent asthma models, alleviating tension in tracheal spirals, and relaxing airway smooth muscle cells (ASMCs). Metallothionein-2 relaxes ASMCs via transgelin-2 (TG2) and induces dephosphorylation of myosin phosphatase target subunit 1 (MYPT1). We identify TSG12 as a nontoxic, specific TG2-agonist that relaxes ASMCs and reduces asthmatic pulmonary resistance. In vivo, TSG12 reduces pulmonary resistance in both ovalbumin- and house dust mite-induced asthma in mice. TSG12 induces RhoA phosphorylation, thereby inactivating the RhoA-ROCK-MYPT1-MLC pathway and causing ASMCs relaxation. TSG12 is more effective than β-agonists in relaxing human ASMCs and pulmonary resistance with potential clinical advantages. These results suggest that TSG12 could be a promising therapeutic approach for treating asthma.

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The major obstacle to use multicores for real-time applications is that we may not predict and provide any guarantee on real-time properties of embedded software on such platforms; the way of handling the on-chip shared resources such as L2 cache may have a significant impact on the timing predictability. In this paper, we propose to use cache space isolation techniques to avoid cache contention for hard realtime tasks running on multicores with shared caches. We present a scheduling strategy for real-time tasks with both timing and cache space constraints, which allows each task to use a fixed number of cache partitions, and makes sure that at any time a cache partition is occupied by at most one running task. In this way, the cache spaces of tasks are isolated at run-time.As technical contributions, we have developed a sufficient schedulability test for non-preemptive fixed-priority scheduling for multicores with shared L2 cache, encoded as a linear programming problem. To improve the scalability of the test, we then present our second schedulability test of quadratic complexity, which is an over approximation of the first test. To evaluate the performance and scalability of our techniques, we use randomly generated task sets. Our experiments show that the first test which employs an LP solver can easily handle task sets with thousands of tasks in minutes using a desktop computer. It is also shown that the second test is comparable with the first one in terms of precision, but scales much better due to its low complexity, and is therefore a good candidate for efficient schedulability tests in the design loop for embedded systems or as an on-line test for admission control.

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