Periodic Hard Real-time Tasks Research Articles

Extensibility-aware Fog Computing Platform configuration for mixed-criticality applications

In this paper, we consider that critical control applications and Fog applications share a Fog Computing Platform (FCP). Critical control applications are implemented as periodic hard real-time tasks and messages and have stringent timing and safety requirements, and require safety certification. Fog applications are implemented as aperiodic tasks and messages and are not critical. Such applications need different approaches to guarantee their timing and dependability requirements. We formulate an optimization problem for the joint configuration of critical control and Fog applications, such that (i) the deadlines and Quality-of-Control (QoC) of control applications are guaranteed at design-time, (ii) the configuration is extensible and supports the addition of future new control applications without requiring costly re-certification, and (iii) the design-time configuration together with the runtime Fog resource management mechanisms, can successfully accommodate multiple dynamic responsive Fog applications. We evaluate our approach on several test cases assuming scenarios for hosting both Fog applications and future critical control applications. The results show that our approach generates extensible schedules which enables Fog nodes to handle Fog applications with a shorter response time and a larger number of future control applications.

A security-aware hardware scheduler for modern multi-core systems with hard real-time constraints

In this paper, we propose an online security-aware hardware scheduler, the so-called Secure And Fast hardware Scheduler (SAFAS), for real-time task scheduling in multi-core systems in the presence of schedule-based side-channel attacks. To avoid such attacks and ensure that all tasks meet their deadlines, SAFAS schedules critical tasks and their replicas using a hardware-based strict Least Slack Time first (LST) algorithm independently while it independently schedules the non-critical tasks using a hardware-based EDF algorithm. SAFAS enhances the system performance and reduces the chance of side-channel attacks due to the different processing cores allocated to each task in each scheduling interval. The hardware scheduler operates independently and in parallel with the multi-core system and hides the scheduling characteristics from adversaries. The software-based Earliest Deadline First (EDF) algorithm is also used for schedulability tests and feasibility analysis of hard real-time periodic tasks to maximize the number of tasks scheduled successfully in the multi-core system. SAFAS has been synthesized and simulated on a Xilinx Vivado 2018.2 and implemented on a Spartan-7 FPGA chip. Our experimental results indicate that SAFAS increases the performance of the system by 4.8 times as compared to previous state-of-the-art hardware schedulers while guaranteeing that all critical tasks and their replicas meet their deadlines.

Low-Power Task Scheduling Algorithm for the Multicore Processor System Based on the Genetic Algorithm

In order to solve the periodic hard real-time tasks with dependencies on multicore processors, the author proposes a low-power task scheduling algorithm for multicore processor systems based on the genetic algorithm. This method first uses the RDAG algorithm to separate the tasks and then takes the lowest power consumption as the principle; a genetic algorithm is used to determine the task mapping. Experimental results show that based on the power consumption model of Intel PXA270, several random task sets are used for simulation experiments, which shows that this method saves 20% to 30% of the energy consumption compared with the existing methods. This method effectively shortens the completion time of tasks, improves the utilization efficiency of multicore system resources, improves the parallel computing capability of multicore systems, reduces the average response time of tasks, and improves the throughput and resource utilization of multicore systems.

Energy aware mixed tasks scheduling in real-time systems

We address the problem of scheduling mixed tasks which consist of n hard real time periodic tasks with shared resources and soft aperiodic tasks and consider two conflicting goals: reducing energy consumption and decreasing response time of aperiodic tasks. Firstly, we compute the optimal speed of periodic tasks and present a novel static mixed task scheduling (SMTS) algorithm. It schedules periodic tasks with the optimal speed and aperiodic tasks with maximum processor speed. Secondly, a dynamic mixed task scheduling (DMTS) algorithm which can reclaim dynamic slack time generated from periodic tasks and the constant bandwidth server to reduce energy consumption is proposed. In addition, it combines dynamic voltage scaling and dynamic power management techniques. Finally, we prove that the DMTS algorithm is feasible. The experimental results show that the DMTS algorithm reduces average 7.18% and 53.66% energy consumption × response time compared with SMTS algorithm and baseline algorithm, respectively.

Feasibility analysis of periodic real-time systems with energy harvesting capabilities

Energy harvesting now appears as a feasible solution to power wireless devices. Such ones including sensor nodes have to be energy neutral i.e. be able to never consume more energy than available. Energy can be drawn from many ambient sources including solar, vibration, etc. Most of wireless devices perform periodic sampling and computations using a microprocessor for real-time monitoring. The software tasks that typically take place in these systems are time critical and cyclic with specified deadlines attached to finishing times. In this paper, we explore the problem of feasibility analysis of hard real-time periodic task sets on a single processor powered by renewable energy. Firstly, we investigate the notion of robustness as the capability of the system to remain stable even in case of positive changes in its operating environment. We prove that our feasibility test is robust with respect to the profile of the energy source. Secondly, we prove that for asynchronous tasks whose initial release times are not known in advance, feasibility can be checked considering the synchronous activation pattern which corresponds to the worst-case scenario. Finally, whenever accurate prediction of the incoming environmental energy is impossible, a sufficient feasibility test with high implementation efficiency is proposed.

Thermal-constrained energy efficient real-time scheduling on multi-core platforms

Abstract As the power density of Integrated Circuit chips continues to grow, energy minimization and temperature reduction are two of the most critical design issues in today’s computer system design. Although energy minimization is closely related to temperature reduction, the most energy-efficient method may not be the most effective one to meet the temperature constraints and vice versa. In this paper, we study the problem of how to partition periodic hard real-time tasks on a multi-core platform to maximize the overall energy efficiency under a peak temperature constraint. Differing from the traditional load-balancing approach, i.e., evenly distributing the workload across the chip, we propose a thermal-balancing strategy, i.e. minimizing the thermal gradient across the active cores, to improve the overall system energy efficiency, especially when the temperature constraints are tight. We first identify the lower bound for energy consumption with this approach, and then transform the task partitioning problem to a variable-sized bin packing problem. We further propose an enhanced algorithm to optimize the task partitioning results. Our simulation results show that the proposed thermal-balancing approach can significantly improve the energy efficiency and task partitioning feasibility for real-time systems with high system utilization and tight temperature constraints.

Improving and Estimating the Precision of Bounds on the Worst-Case Latency of Task Chains

One major issue that hinders the use of performance analysis in industrial design processes is the pessimism inherent to any analysis technique that applies to realistic system models. Indeed, such analyses may conservatively declare unschedulable systems that will in fact never miss any deadlines. We advocate the need to compute not only tight upper bounds on worst-case behaviors but also tight lower bounds. As a first step, we focus on uniprocessor systems executing a set of sporadic or periodic hard real-time task chains. Each task has its own priority, and the chains are scheduled according to the fixed-priority pre-emptive scheduling policy. Computing the worst-case end-to-end latency (WCEL) of each chain is complex because of the intricate relationship between the task priorities. Compared to the state of the art, our analysis provides upper bounds on the WCEL in the more general case of asynchronous task chains, and also provides lower bounds on the WCEL both for synchronous and asynchronous chains. Our computed lower bounds correspond to actual system executions exhibiting a behavior that is as close to the worst case as possible, while all other approaches rely on simulations. Extensive experiments show the relevance of lower bounds on the worst-case behavior for the industrial design of real-time embedded systems.

Run-Time Management for Multicore Embedded Systems With Energy Harvesting

In this paper, we propose a novel framework for runtime energy and workload management in multicore embedded systems with solar energy harvesting and a periodic hard real-time task set as the workload. Compared with prior work, our framework makes several novel contributions and possesses several advantages, including the following: 1) a semidynamic scheduling heuristic that dynamically adapts to runtime harvested power variations without losing the consistency of periodic tasks; 2) a battery-supercapacitor hybrid energy storage module for more efficient system energy management; 3) a coarse-grained core shutdown heuristic for additional energy saving; 4) energy budget planning and task allocation heuristics with process variation tolerance; 5) a novel dual-speed method specifically designed for periodic tasks to address discrete frequency levels and dynamic voltage/frequency scaling switching overhead at the core level; and 6) an extension to prepare the system for thermal issues arising at runtime during extreme environmental conditions. The experimental studies show that our framework results in a reduction in task miss rate by up to 70% and task miss penalty by up to 65% compared with the best known prior work.

Scheduling Dynamic Hard Real-Time Task Sets on Fully and Partially Reconfigurable Platforms

Reconfigurable systems are increasingly being employed in a large class of today's heterogeneous real-time embedded systems which often demand satisfaction of stringent timeliness constraints. However, executing a set of hard real-time applications on reconfigurable systems such that all timing constraints are satisfied while also allowing efficient resource utilization requires effective scheduling, mapping and admission control strategies. This letter presents methodologies for scheduling periodic hard real-time dynamic task sets on fully and partially reconfigurable field-programmable gate arrays (FPGAs). The floor of the FPGA is assumed to be statically equipartitioned into a set of homogeneous tiles (each of which act as individual processing elements or PEs) such that any arbitrary task of the given task set may be feasibly mapped into the area of a given tile. Experimental results reveal that the proposed algorithms are able to achieve high resource utilization with low task rejection rates over a variety of simulation scenarios.

Energy-Efficient Real-Time Scheduling of Tasks with Abortable Critical Sections

In this paper, an energy-efficient scheduling algorithm, called ceiling-based conditional abortable scheduling (CB-CAS) algorithm, is proposed to schedule periodic hard real-time tasks in a non-ideal DVS processor. Based on the schedulability analysis, CB-CAS calculates a proper processor speed for task execution so that the energy consumption can be reduced without violating the timing constraints of tasks. For saving more energy, we also assume that the critical sections of tasks are abortable, which is a strategy originally proposed to reduce priority inversions. In this paper, CB-CAS introduces a conditional abort rule and a dynamic speed adjustment method to work with the rate monotonic scheduling algorithm and the priority ceiling protocol so that the energy consumption could be reduced further. Whenever two tasks are conflicting for the same resource, CB-CAS will examine the cost of blocking the higher-priority task and the cost of aborting the lower-priority task. CB-CAS will abort the lower-priority task and adjust the processor speed dynamically only if it is more energy efficient. The schedulability analysis and the properties of CB-CAS are given in this paper. The capabilities of CB-CAS were also evaluated by a series of experiments, for which we have some encouraging results.

Efficient Scheduling Algorithm for Hard Real-Time Tasks in Primary-Backup Based Multiprocessor Systems

针对基于主副版本容错的多处理机中独立的、抢占性的硬实时任务,提出了一种高效的调度算法——TPFTRM(task partition based fault tolerant rate-monotonic)算法.该算法将单机实时RM 算法扩展到容错多处理机上,并且调度过程中从不使用主动执行的任务副版本,而仅使用被动执行和主副重叠方式执行的任务副版本,从而最大限度地利用副版本重叠和分离技术提高了算法调度性能.此外,TPFTRM 根据任务负载不同将任务集合划分成两个不相交的子集进行分配;还根据处理机调度的任务版本不同,将处理机集合划分成3 个不相交的子集进行调度,从而使TPFTRM 调度算法便于理解、实现以及减少了调度所需要的运行时间.模拟实验对各种具有不同周期和任务负载的任务集合进行了调度测试.实验结果表明,TPFTRM与目前所知同类算法相比,在调度相同参数的任务集合时不仅明显减少了调度所需要的处理机数目,还减少了调度所需要的运行时间,从而证实了TPFTRM 算法的高效性.;This paper has considered the problem of preemptively scheduling a set of independent periodic hard real-time tasks in primary-backup based multiprocessor systems. An efficient scheduling algorithm—Task Partition based Fault Tolerant Rate-Monotonic (TPFTRM) is proposed which extends RM algorithm to primary-backup based multiprocessor to provide fault tolerance. Compared with previous scheduling algorithms in this area, TPFTRM abandons active backup copies and only uses passive and overlapping backup copies to maximize the backup over-booking and deallocation, thus improves the scheduling performance. Moreover, TPFTRM proposes the task partitioning and processors grouping technique, which reduce the scheduling computation time and also make an easy way to understand and implement it. Extensive simulations experiments are also carried out based on task sets with different parameters. And the simulation result shows a remarkable saving of processors as well as scheduling computation time compared with previous algorithms, which proves the feasibility and effectiveness of the oposed TPFTRM algorithm.

The One-Shot Task Model for Robust Real-Time Embedded Control Systems

Embedded control systems are often implemented in small microprocessors enabled with real-time technology. In this context, control laws are often designed according to discrete-time control systems theory and implemented as hard real-time periodic tasks. Standard discrete-time control theory mandates to periodically sample (input) and actuate (output). Depending on how input/output (I/O) operations are performed within the hard real-time periodic task, different control task models can be distinguished. However, existing task models present important drawbacks. They generate task executions prone to violate the periodic control demands, a problem known as sampling and latency jitter, or they impose synchronized I/O operations at each task job execution that produce a constant but artificially long I/O latency. In this paper, the one-shot task model for implementing control systems in embedded multitasking hard real-time platforms is presented. The novel control task model is built upon control theoretical results that indicate that standard control laws can be implemented considering only periodic actuation. Taking advantage of this property, the one-shot task model is shown to remove endemic problems for real-time control systems such as sampling and latency jitters. In addition, it can minimize the harmful effects that long I/O latencies have on control performance. Extensive simulations and real experiments show the feasibility and effectiveness of the novel task model, compared to previous real-time and/or control-based solutions.

Feasibility analysis of hard real-time periodic tasks

The problem of determining the feasibility of hard real-time periodic tasks is known to be co-NP-complete when there exists a task with relative deadline shorter than its period. Thus “Processor Demand Approach (PDA)” for synchronous task sets has been considered as a practical tool to solve the feasibility problem. PDA determines the feasibility of a task set by checking whether there exists a task whose deadline is missed by a certain time which is computed based on the characteristic of the task set. In this paper, we present a new method for feasibility test by combining PDA with the analysis methods for aperiodic scheduling. It is shown that the number of tests required of the new method to determine the feasibility is never greater than the smallest number of tests the existing algorithm requires. Although our method has pseudo-polynomial time complexity, experimental results show that the new method requires significantly less computation to determine feasibility.

Feasibility analysis of hard real-time periodic tasks

The problem of determining the feasibility of hard real-time periodic tasks is known to be co-NP-complete when there exists a task with relative deadline shorter than its period. Thus Processor Demand Approach (PDA) for synchronous task sets has been considered as a practical tool to solve the feasibility problem. PDA determines the feasibility of a task set by checking whether there exists a task whose deadline is missed by a certain time which is computed based on the characteristic of the task set. In this paper, we present a new method for feasibility test by combining PDA with the analysis methods for aperiodic scheduling. It is shown that the number of tests required of the new method to determine the feasibility is never greater than the smallest number of tests the existing algorithm requires. Although our method has pseudo-polynomial time complexity, experimental results show that the new method requires significantly less computation to determine feasibility.

A fault-tolerant scheduling algorithm for real-time periodic tasks with possible software faults

A hard real-time system is usually subject to stringent reliability and timing constraints. One way to avoid missing deadlines is to trade the quality of computation results for timeliness, and software fault tolerance is often achieved with the use of redundant programs. A deadline mechanism which combines these two methods is proposed to provide software fault tolerance in hard real-time periodic task systems. We consider the problem of scheduling a set of real-time periodic tasks each of which has two versions: primary and alternate. The primary version contains more functions and produces good quality results, but its correctness is more difficult to verify. The alternate version contains only the minimum required functions and produces less precise results and its correctness is easy to verify. We propose a scheduling algorithm which 1) guarantees either the primary or alternate version of each critical task to be completed in time and 2) attempts to complete as many primaries as possible. Our basic algorithm uses a fixed priority-driven preemptive scheduling scheme to preallocate time intervals to the alternates and, at runtime, attempts to execute primaries first. An alternate will be executed only if necessary because of time or bugs.

Scheduling of Offset Free Systems

In this paper, we study the problem of scheduling hard real-time periodic tasks. We consider independent tasks which are characterized by a period, a hard deadline and a computation time, but where the offsets may be chosen by the scheduling algorithm. We first show that we can restrict the problem by considering non-equivalent offset assignments. More precisely, we show that there are finitely many non-equivalent offset assignments and we propose a method to reduce significantly this number and consider only the minimal number of non-equivalent offset assignments. We then propose an optimal offset assignment rule which considers only the non-equivalent offset assignments. However the number of combinations remains exponential; for this reason, we also propose a nearly optimal algorithm with a more reasonable time complexity.

Liu and Layland's schedulability test revisited

In this paper, we study the problem of scheduling hard real-time periodic task sets on a single processor with the rate monotonic scheduler. We are concerned with the feasibility test given by Liu and Layland, based on the least upper bound of the utilization factor. We show that the result is incomplete and that the argument is incorrect. We complete and correct the result.

General Response Time Computation for the Deadline Driven Scheduling of Periodic Tasks

In this paper we study the problem of scheduling hard real-time periodic task sets with a dynamic and preemptive scheduler. We will focus on the response time notion, its interest and its effective computation for the deadline driven scheduler. We present a general calculation procedure for determining the response time of the k th request of a task in asynchronous systems with general as well as arbitrary deadlines. Finally, we analyze the performance of the computation so defined, both in terms of time and memory requirements.

Developing predictable and flexible distributed real-time systems

Predictability is considered the most distinguishing characteristic of real-time systems. Besides that, adaptability is also a very important attribute because RT systems are usually designed for long life cycles, during which they will have to cope with change. This paper presents the STER real-time software development environment, designed to support the production of predictable, and yet flexible, distributed real-time systems. Flexibility is one of the main concerns of STER’s programming model, based on the construction of reusable software modules. Modules can be reused with different timing constraints without having to be recoded, since the specification of their timing constraints is decoupled from their implementation. Predictable temporal behavior is obtained by an integrated allocation and scheduling strategy that involves off-line and online schedulers. The off-line scheduler tries to satisfy timing, precedence and allocation constraints of periodic hard real-time tasks, and to give the necessary leeway for the dynamic scheduling of aperiodic tasks. The paper shows how distributed programs are translated to scheduling graphs, and gives the results of some experiments conducted to evaluate the performance of the off-line algorithm.

The Slack Method: A New Method for Static Allocation ofHard Real-Time Tasks

This article presents and evaluates the Slack Method, a new constructive heuristic for the allocation (mapping) of periodic hard real-time tasks to multiprocessor or distributed systems. The Slack Method is based on task deadlines, in contrast with other constructive heuristics, such as List Processing. The presented evaluation shows that the Slack Method is superior to list-processing-based approaches with regard to both finding more feasible solutions as well as finding solutions with better objective function values. In a comparative survey we evaluate the Slack Method against several alternative allocation techniques. This includes comparisons with optimal algorithms, non-guided search heuristics (e.g. Simulated Annealing), and other constructive heuristics. The main practical result of the comparison is that a combination of non-guided search and constructive approaches is shown to perform better than either of them alone, especially when using the Slack Method.