MORA: an Energy-Aware Slack Reclamation Scheme for Scheduling Sporadic Real-Time Tasks upon Multiprocessor Platforms

In this paper, we address the global and preemptive energy-aware scheduling problem of sporadic constrained-deadline tasks on DVFS-identical multiprocessor platforms. We propose an online slack reclamation scheme which profits from the discrepancy between the worst- and actual-case execution time of the tasks by slowing down the speed of the processors in order to save energy. Our algorithm called MORA takes into account the application-specific consumption profile of the tasks. We demonstrate that MORA does not jeopardize the system schedulability and we show by performing simulations that it can save up to 32% of energy (in average) compared to execution without using any energy-aware algorithm.Comment: 11 page

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

Refinement of Workload Models for Engine Controllers by State Space Partitioning

We study an engine control application where the behavior of engine controllers depends on the engine\u27s rotational speed. For efficient and precise timing analysis, we use the Digraph Real-Time (DRT) task model to specify the workload of control tasks where we employ optimal control theory to faithfully calculate the respective minimum inter-release times. We show how DRT models can be refined by finer grained partitioning of the state space of the engine up to a model which enables an exact timing analysis. Compared to previously proposed methods which are either unsafe or pessimistic, our work provides both abstract and tight characterizations of the corresponding workload

High Performance dynamic voltage/frequency scaling algorithm for real-time dynamic load management and code mobility

Modern cyber-physical systems assume a complex and dynamic interaction between the real world and the computing system in real-time. In this context, changes in the physical environment trigger changes in the computational load to execute. On the other hand, task migration services offered by networked control systems require also management of dynamic real-time computing load in nodes. In such systems it would be difficult, if not impossible, to analyse off-line all the possible combinations of processor loads. For this reason, it is worthwhile attempting to define new flexible architectures that enable computing systems to adapt to potential changes in the environment. We assume a system composed by three main components: the first one is responsible of the management of the requests arisen when new tasks require to be executed. This management component asks to the second component about the resources available to accept the new tasks. The second component performs a feasibility analysis to determine if the new tasks can be accepted coping with its real-time constraints. A new processor speed is also computed. A third component monitors the execution of tasks applying a fixed priority scheduling policy and additionally controlling the frequency of the processor. This paper focus on the second component providing a "correct" (a task never is accepted if it is not schedulable) and "near-exact" (a task is rarely rejected if it is schedulable) algorithm that can be applicable in practice because its low/medium and predictable computational cost. The algorithm analyses task admission in terms of processor frequency scaling. The paper presents the details of a novel algorithm to analyse tasks admission and processor frequency assignment. Additionally, we perform several simulations to evaluate the comparative performance of the proposed approach. This evaluation is made in terms of energy consumption, task rejection ratios, and real computing costs. The results of simulations show that from the cost, execution predictability, and task acceptance points of view, the proposed algorithm mostly outperforms other constant voltage scaling algorithms. © 2011 Elsevier Inc. All rights reserved.This work has been supported by the Spanish Government as part of the SIDIRELI project (DPI2008-06737-C02-02), COBAMI project (DPI2011-28507-C02-02) and by the Generalitat Valenciana (Project ACOMP-2010-038).Coronel Parada, JO.; Simó Ten, JE. (2012). High Performance dynamic voltage/frequency scaling algorithm for real-time dynamic load management and code mobility. Journal of Systems and Software. 85(4):906-919. https://doi.org/10.1016/j.jss.2011.11.284S90691985

CPU Energy-Aware Parallel Real-Time Scheduling

Both energy-efficiency and real-time performance are critical requirements in many embedded systems applications such as self-driving car, robotic system, disaster response, and security/safety control. These systems entail a myriad of real-time tasks, where each task itself is a parallel task that can utilize multiple computing units at the same time. Driven by the increasing demand for parallel tasks, multi-core embedded processors are inevitably evolving to many-core. Existing work on real-time parallel tasks mostly focused on real-time scheduling without addressing energy consumption. In this paper, we address hard real-time scheduling of parallel tasks while minimizing their CPU energy consumption on multicore embedded systems. Each task is represented as a directed acyclic graph (DAG) with nodes indicating different threads of execution and edges indicating their dependencies. Our technique is to determine the execution speeds of the nodes of the DAGs to minimize the overall energy consumption while meeting all task deadlines. It incorporates a frequency optimization engine and the dynamic voltage and frequency scaling (DVFS) scheme into the classical real-time scheduling policies (both federated and global) and makes them energy-aware. The contributions of this paper thus include the first energy-aware online federated scheduling and also the first energy-aware global scheduling of DAGs. Evaluation using synthetic workload through simulation shows that our energy-aware real-time scheduling policies can achieve up to 68% energy-saving compared to classical (energy-unaware) policies. We have also performed a proof of concept system evaluation using physical hardware demonstrating the energy efficiency through our proposed approach

A Survey of Schedulability Analysis Techniques for Rate-Dependent Tasks

In automotive embedded real-time systems, such as the engine control unit, there are tasks that are activated whenever the crankshaft arrives at a specific angular position. As a consequence the frequency of activation changes with the crankshaft’s angular speed (i.e., engine rpm). Additionally, execution times and deadlines may also depend on angular speeds and positions. This paper provides a survey on schedulability analysis techniques for tasks with this rate-dependent behaviour. It covers different task-models and analysis methods for both fixed priority and earliest deadline first scheduling. A taxonomy of the different analysis methods, classifying them according to the assumptions made and the precision of the analysis, is provided at the end of the pape

A real-time scheduling simulator for engine control application

Implementazione di uno strumento di simulazione di scheduling real-time, con estensione per task Adaptive Variable Rate. Analisi dei risultati ottenuti dalle simulazioni, nelle quali vengono confrontati i due algoritmi EDF e Fixed Priority, in particolare considerando la schedulability come parametro di confronto

smARTflight: An Environmentally-Aware Adaptive Real-Time Flight Management System

Multi-rotor drones require real-time sensor data processing and control to maintain flight stability, which is made more challenging by external disturbances such as wind. In this paper we introduce smARTflight: an environmentally-aware adaptive real-time flight management system. smARTflight adapts the execution frequencies of flight control tasks according to timing and safety-critical constraints, in response to transient fluctuations of a drone’s attitude. In contrast to current state-of-the-art methods, smARTflight’s criticality-aware scheduler reduces the latency to return to a steady-state target attitude. The system also improves the overall control accuracy and lowers the frequency of adjustments to motor speeds to conserve power. A comparative case-study with a well-known autopilot shows that smARTflight reduces unnecessary control loop executions under stable conditions, while reducing response time latency by as much as 60% in a given axis of rotation when subjected to a 15° step attitude disturbance.https://www.cs.bu.edu/fac/richwest/papers/smARTflight-ecrts20.pdfhttps://drops.dagstuhl.de/opus/volltexte/2020/12387/pdf/LIPIcs-ECRTS-2020-24.pdfPublished versio

Network Service Customization: End-Point Perspective (Proposal)

An important problem with cell-switched technologies such as Asynchronous Transfer Mode (ATM) is the provision of customized multiplexing behavior to applications. This customization takes the form of setting up processes in the network and end-points to meet application Quality of Service (QoS) requirements. The proposed thesis work examines the necessary components of a software architecture to provide QoS in the end-points of a cell-switched network. An architecture has been developed, and the thesis work will refine it using a driving application of the full-feedback teleoperation of a robotics system. Preliminary experimental results indicate that such teleoperation is possible using general-purpose workstations and a lightly-loaded ATM link. An important result of the experimental portion of the thesis work will be a study of the domain of applicability for various resource management techniques