Ambient assisted living (AAL) is focused on providing assistance to people primarily in their natural environment. Over the past decade, the AAL domain has evolved at a fast pace in various directions. The stakeholders of AAL are not only limited to patients, but also include their relatives, social services, health workers, and care agencies. In fact, AAL aims at increasing the life quality of patients, their relatives and the health care providers with a holistic approach. This paper aims at providing a comprehensive overview of the AAL domain, presenting a systematic analysis of over 10 years of relevant literature focusing on the stakeholders' needs, bridging the gap of existing reviews which focused on technologies. The findings of this review clearly show that until now the AAL domain neglects the view of the entire AAL ecosystem. Furthermore, the proposed solutions seem to be tailored more on the basis of the available existing technologies, rather than supporting the various stakeholders' needs. Another major lack that this review is pointing out is a missing adequate evaluation of the various solutions. Finally, it seems that, as the domain of AAL is pretty new, it is still in its incubation phase. Thus, this review calls for moving the AAL domain to a more mature phase with respect to the research approaches
This article presents a survey of energy-aware scheduling algorithms proposed for real-time systems. The analysis presents the main results starting from the middle 1990s until today, showing how the proposed solutions evolved to address the evolution of the platform's features and needs. The survey first presents a taxonomy to classify the existing approaches for uniprocessor systems, distinguishing them according to the technology exploited for reducing energy consumption, that is, Dynamic Voltage and Frequency Scaling (DVFS), Dynamic Power Management (DPM), or both. Then, the survey discusses the approaches proposed in the literature to deal with the additional problems related to the evolution of computing platforms toward multicore architectures.
Abstract-A central issue for verifying the schedulability of hard realtime systems is the correct evaluation of task execution times. These values are significantly influenced by the preemption overhead, which mainly includes the cache related delays and the context switch times introduced by each preemption. Since such an overhead significantly depends on the particular point in the code where preemption takes place, this paper proposes a method for placing suitable preemption points in each task in order to maximize the chances of finding a schedulable solution.In a previous work, we presented a method for the optimal selection of preemption points under the restrictive assumption of a fixed preemption cost, identical for each preemption point. In this paper, we remove such an assumption, exploring a more realistic and complex scenario where the preemption cost varies throughout the task code. Instead of modeling the problem with an integer programming formulation, with exponential worst-case complexity, we derive an optimal algorithm that has a linear time and space complexity. This somewhat surprising result allows selecting the best preemption points even in complex scenarios with a large number of potential preemption locations. Experimental results are also presented to show the effectiveness of the proposed approach in increasing the system schedulability.
Abstract-Applying classical dynamic voltage scaling (DVS)techniques to real-time systems running on processors with discrete voltage/frequency modes causes a waste of computational resources. In fact, whenever the ideal speed level computed by the DVS algorithm is not available in the system, to guarantee the feasibility of the task set, the processor speed must be set to the nearest level greater than the optimal one, thus underutilizing the system. Whenever the task set allows a certain degree of flexibility in specifying timing constraints, rate adaptation techniques can be adopted to balance performance (which is a function of task rates) versus energy consumption (which is a function of the processor speed).In this paper, we propose a new method that combines discrete DVS management with elastic scheduling to fully exploit the available computational resources. Depending on the application requirements, the algorithm can be set to improve performance or reduce energy consumption, so enhancing the flexibility of the system. A reclaiming mechanism is also used to take advantage of early completions. To make the proposed approach usable in real-world applications, the task model is enhanced to consider some of the real CPU characteristics, such as discrete voltage/frequency levels, switching overhead, task execution times nonlinear with the frequency, and tasks with different power consumption. Implementation issues and experimental results for the proposed algorithm are also discussed.
Computing platforms are evolving towards heterogeneous architectures including processors of different types and field programmable gate arrays (FPGAs), used as hardware accelerators for speeding up specific functions. The increasing capacity and performance of modern FPGAs, with their partial reconfiguration capabilities, have made them attractive in several application domains, including space applications.This paper proposes a framework for supporting the development of safety-critical real-time systems that exploit hardware accelerators developed through FPGAs with dynamic partial reconfiguration capabilities.A model is first presented and then used to derive a response-time analysis to verify the schedulability of a real-time task set under given constraints and assumptions. Although the analysis is based on a generic model, the proposed framework has been conceived to account for several real-world constraints present on today's platforms and has been practically validated on the Zynq platform, showing that it can actually be supported by state-of-the-art technologies. Finally, a number of experiments are reported to evaluate the worst-case performance of the proposed approach on synthetic workload
Abstract-Limited preemption scheduling has been introduced as a viable alternative to non-preemptive and fullypreemptive scheduling when reduced blocking times need to coexist with an acceptable context switch overhead. To achieve this goal, preemptions are allowed only at selected points of the code of each task, decreasing the preemption overhead and simplifying the estimation of worst-case execution parameters. Unfortunately, the problem of how to place these preemption points is rather complex and has not been solved.In this paper, a method is presented for the optimal placement of preemption points under simplifying conditions, namely, a fixed preemption overhead at each point. We will prove that if our method is not able to produce a feasible schedule, then no other possible preemption point placement (including non-preemptive and fully preemptive scheduling) can find a schedulable solution. The presented method is general enough to be applicable to both EDF and Fixed Priority scheduling, with limited modifications.
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