A Practical Framework to Study Low-Power Scheduling Algorithms on Real-Time and Embedded Systems

With the advanced technology used to design VLSI (Very Large Scale Integration) circuits, low-power and energy-efficiency have played important roles for hardware and software implementation. Real-time scheduling is one of the fields that has attracted extensive attention to design low-power, embedded/real-time systems. The dynamic voltage scaling (DVS) and CPU shut-down are the two most popular techniques used to design the algorithms. In this paper, we firstly review the fundamental advances in the research of energy-efficient, real-time scheduling. Then, a unified framework with a real Intel PXA255 Xscale processor, namely real-energy, is designed, which can be used to measure the real performance of the algorithms. We conduct a case study to evaluate several classical algorithms by using the framework. The energy efficiency and the quantitative difference in their performance, as well as the practical issues found in the implementation of these algorithms are discussed. Our experiments show a gap between the theoretical and real results. Our framework not only gives researchers a tool to evaluate their system designs, but also helps them to bridge this gap in their future works

A Survey of Techniques For Improving Energy Efficiency in Embedded Computing Systems

Recent technological advances have greatly improved the performance and features of embedded systems. With the number of just mobile devices now reaching nearly equal to the population of earth, embedded systems have truly become ubiquitous. These trends, however, have also made the task of managing their power consumption extremely challenging. In recent years, several techniques have been proposed to address this issue. In this paper, we survey the techniques for managing power consumption of embedded systems. We discuss the need of power management and provide a classification of the techniques on several important parameters to highlight their similarities and differences. This paper is intended to help the researchers and application-developers in gaining insights into the working of power management techniques and designing even more efficient high-performance embedded systems of tomorrow

Low-energy standby-sparing for hard real-time systems

Time-redundancy techniques are commonly used in real-time systems to achieve fault tolerance without incurring high energy overhead. However, reliability requirements of hard real-time systems that are used in safety-critical applications are so stringent that time-redundancy techniques are sometimes unable to achieve them. Standby sparing as a hardwareredundancy technique can be used to meet high reliability requirements of safety-critical applications. However, conventional standby-sparing techniques are not suitable for lowenergy hard real-time systems as they either impose considerable energy overheads or are not proper for hard timing constraints. In this paper we provide a technique to use standby sparing for hard real-time systems with limited energy budgets. The principal contribution of this work is an online energymanagement technique which is specifically developed for standby-sparing systems that are used in hard real-time applications. This technique operates at runtime and exploits dynamic slacks to reduce the energy consumption while guaranteeing hard deadlines. We compared the low-energy standby-sparing (LESS) system with a low-energy timeredundancy system (from a previous work). The results show that for relaxed time constraints, the LESS system is more reliable and provides about 26% energy saving as compared to the time-redundancy system. For tight deadlines when the timeredundancy system is not sufficiently reliable (for safety-critical application), the LESS system preserves its reliability but with about 49% more energy consumptio

Real-Time Task Scheduling under Thermal Constraints

As the speed of integrated circuits increases, so does their power consumption. Most of this power is turned into heat, which must be dissipated effectively in order for the circuit to avoid thermal damage. Thermal control therefore has emerged as an important issue in design and management of circuits and systems. Dynamic speed scaling, where the input power is temporarily reduced by appropriately slowing down the circuit, is one of the major techniques to manage power so as to maintain safe temperature levels. In this study, we focus on thermally-constrained hard real-time systems, where timing guarantees must be met without exceeding safe temperature levels within the microprocessor. Speed scaling mechanisms provided in many of today’s processors provide opportunities to temporarily increase the processor speed beyond levels that would be safe over extended time periods. This dissertation addresses the problem of safely controlling the processor speed when scheduling mixed workloads with both hard-real-time periodic tasks and non-real-time, but latency-sensitive, aperiodic jobs. We first introduce the Transient Overclocking Server, which safely reduces the response time of aperiodic jobs in the presence of hard real-time periodic tasks and thermal constraints. We then propose a design-time (off-line) execution-budget allocation scheme for the application of the Transient Overclocking Server. We show that there is an optimal budget allocation which depends on the temporal character istics of the aperiodic workload. In order to provide a quantitative framework for the allocation of budget during system design, we present a queuing model and validate the model with results from a discrete-event simulator. Next, we describe an on-line thermally-aware transient overclocking method to reduce the response time of aperiodic jobs efficiently at run-time. We describe a modified Slack-Stealing algorithm to consider the thermal constraints of systems together with the deadline constraints of periodic tasks. With the thermal model and temperature data provided by embedded thermal sensors, we compute slack for aperiodic workload at run-time that satisfies both thermal and temporal constraints. We show that the proposed Thermally-Aware Slack-Stealing algorithm minimizes the response times of aperiodic jobs while guaranteeing both the thermal safety of the system and the schedulability of the real-time tasks. The two proposed speed control algorithms are examples of so-called proactive schemes, since they rely on a prediction of the thermal trajectory to control the temperature before safe levels are exceeded. In practice, the effectiveness of proactive speed control for the thermal management of a system relies on the accuracy of the thermal model that underlies the prediction of the effects of speed scaling and task execution on the temperature of the processor. Due to variances in the manufacturing of the circuit and of the environment it is to operate, an accurate thermal model can be gathered at deployment time only. The absence of power data makes a straightforward derivation of a model impossible. We, therefore, study and describe a methodology to infer efficiently the thermal model based on the monitoring of system temperatures and number of instructions used for task executions

Dynamic scheduling techniques for adaptive applications on real-time embedded systems

Ph.DDOCTOR OF PHILOSOPH

Mixed Criticality Systems - A Review : (13th Edition, February 2022)

This review covers research on the topic of mixed criticality systems that has been published since Vestal’s 2007 paper. It covers the period up to end of 2021. The review is organised into the following topics: introduction and motivation, models, single processor analysis (including job-based, hard and soft tasks, fixed priority and EDF scheduling, shared resources and static and synchronous scheduling), multiprocessor analysis, related topics, realistic models, formal treatments, systems issues, industrial practice and research beyond mixed-criticality. A list of PhDs awarded for research relating to mixed-criticality systems is also included

Efficient Allocation And Enforcement Of Interfaces In Compositional Real-Time Systems

Compositional real-time research has become one of the emerging trends in embedded and real-time systems due to the increasing scale and complexity of such systems. In this design paradigm, a large system is decomposed into smaller and simpler components, each of which abstracts their temporal requirements via interfaces. Such systems are mostly implemented by resource partitions to ensure that the components receive resources according to their interfaces. Potential implementations of a resource partition are via server-based interfaces or demand-based interfaces. In this context, our thesis in this dissertation is as follows: Currently, server-based interfaces ensure strong temporal isolation among components at the cost of resource over-provisioning whereas demand-based interfaces precisely model the resource demand of a component without the guarantee of temporal isolation. For both these models, efficient and effective resource allocation as well as strict temporal isolation among components can be achieved. Specifically, we can obtain efficient and near-optimal bandwidth allocation schemes and admission controllers for periodic resource model and arbitrary demand-based interface respectively. Furthermore, efficient slack reclamation technique can be obtained to allocate unused processing resources at runtime while still enforcing the given interface. To support our thesis, we address efficient resource allocation among components with server-based interfaces by providing fully-polynomial-time approximation schemes (FPTAS) for allocating processing resource to components scheduled by earliest-deadline-first (EDF) or fixed-priority (FP) scheduling algorithm. For enforcing temporal isolation of demand-based interfaces, we provide a parametric approximate admission control algorithm, which has polynomial-time complexity in terms of number of active jobs in the system and the approximation parameter. Finally, to address efficient reclamation of unused processing resources, we give a novel technique to optimally and efficiently determine maximum allowable runtime slack for a component with arbitrary interface, considering active jobs in the system and guaranteeing system schedulability even for worst-case future job arrival scenarios. We expect that these techniques can ultimately be used to minimize the size, weight, and power requirements of real-time and embedded systems by reducing the processing resource requirements of such systems