Mauro Marinoni

Elastic DVS Management in Processors With Discrete Voltage/Frequency Modes

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

Preemption Points Placement for Sporadic Task Sets

Limited preemption scheduling has been introduced as a viable alternative to non-preemptive and fully preemptive 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.

Exploring the ambient assisted living domain: a systematic review

AbstractAmbient 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.

Energy-Aware Scheduling for Real-Time Systems: A Survey

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 platforms 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.

Non-preemptive interrupt scheduling for safe reuse of legacy drivers in real-time systems

Low-level support of peripheral devices is one of the most demanding activities in a real-time operating system. In fact, the rapid development of new interface boards causes a tremendous effort at the operating system level for writing and testing low-level drivers for supporting the new hardware. The possibility of reusing legacy drivers in real-time systems would offer the great advantage of keeping the rate of changes with a small programming effort. Since typical legacy drivers are written to execute in a non-preemptive fashion, a suitable operating system mechanism is needed to protect real-time application tasks from unpredictable bursty interrupt requests. In this paper, we present a novel approach suitable for scheduling interrupt service routines. Main features of the method include: high priority of the handler, non preemptive execution, bandwidth reservation for the application tasks, and independence of the interrupt service policy from the scheduling policy adopted for the application tasks.

Exact Interference of Adaptive Variable-Rate Tasks under Fixed-Priority Scheduling

Engine control applications require the execution of tasks activated in relation to specific system variables, such as the crankshaft rotation angle. To prevent possible overload conditions at high rotation speeds, such tasks are designed to vary their functionality (hence their computational requirements) for different speed ranges. Modeling and analyzing such a type of tasks poses new research challenges in the schedulability analysis that are now being addressed in the real-time literature. This paper advances the state of the art by presenting a method for computing the exact worst-case interference of such adaptive variable-rate tasks under fixed priority scheduling, enabling a tight analysis and design of engine control applications.

Tracking limbs motion using a wireless network of inertial measurement units

Tracking the position and the orientation of human limbs to reconstruct postures and actions is becoming a crucial need in several application domains, including medicine, rehabilitation, sport, and games. However, most available solutions are expensive, imprecise, or require an instrumentation of the environment. This paper presents a low-cost tracking system based on a set of wearable inertial measurement units (IMUs) coordinated as a wireless body area network. After the system description, the characterization of the single node is provided through a set of experiments. Issues related to real-time processing, calibration, data synchronization, and energy consumption are introduced using a preliminary simplified setup with two nodes.

An energy-aware algorithm exploiting limited preemptive scheduling under fixed priorities

This paper presents a new energy-aware algorithm that integrates Dynamic Voltage and Frequency Scaling (DVFS) and Dynamic Power Management (DPM) techniques to further reduce energy consumption in embedded systems. It consists of an off-line DVFS-stage, for computing the speed that minimizes energy consumption during active intervals while guaranteeing timing constraints, and an online DPM-stage, for prolonging sleep intervals by postponing task execution. Moreover, limited preemptive scheduling is exploited to reduce preemption costs and further extend sleep intervals under fixed-priority systems, with respect to fully preemptive schedulers. The online algorithm has a constant complexity and preemption costs are taken into account in the analysis. A set of simulation experiments are reported to illustrate the behavior of the proposed approach as a function of different parameters and compare its performance with the state-of-art methods available in the literature.

Energy-aware packet and task co-scheduling for embedded systems

A crucial objective in battery operated embedded systems is to work under the minimal power consumption that provides a desired level of performance. Dynamic Voltage Scaling (DVS) and Dynamic. Power Management (DPM) are typical techniques used on processors and devices to reduce the power consumption through speed variations and power switching, respectively. The effectivenes of both DVS and DPM needs to be considered in the development of a power management policy for a system that consists of both DVS-enabled and DPM-enabled components. This paper explores how to efficiently reduce the power consumption of real-time applications with constrained resources, like energy, CPU, and transmission bandwidth. A combined DVS-DP approach with a reduced complexity is proposed to make use of online strategies for embedded systems. Simulation results reveal the effectiveness of the proposed approach.

A Framework for Supporting Real-Time Applications on Dynamic Reconfigurable FPGAs

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 todays 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.