Energy aware fixed priority scheduling in mixed-criticality systems

Most of studies about energy management for MC systems are based on dynamic priority scheme. The disadvantages of dynamic priority scheme are high system overhead and poor predictability. Unlike previous studies, we focus on the problem of scheduling mixed-criticality (MC) periodic tasks with minimizing energy consumption in MC systems based on fixed priority scheme. Firstly, we explain a criticality rate monotonic scheduling (CRMS) and propose the sufficient schedulability condition of CRMS. Secondly, we compute the energy minimization uniform scaled speed and present an optimal static solution algorithm based on CRMS. The extra workload of the high criticality level (HI) task executes with the maximum processor speed in the high criticality mode (HI-mode). But this algorithm does not exploit the slack time generated from the HI task in the low criticality mode (LO-mode). For energy efficiency, we propose a dynamic fixed priority energy minimization algorithm which exploits the slack time generated from the HI task in LO-mode to save energy. In addition, it combines a dynamic voltage and frequency scaling technique and a dynamic power management technique to reduce energy consumption. Finally, the experiments are applied to evaluate the performance of the proposed algorithm and the experimental results show that the proposed algorithm can save up 23.89% energy compared with other existing algorithms.     

固定优先级调度的线性近似分析方法

通过线性逼近硬实时系统任务的工作负荷量的方法,一个更加接近精确响应时间的时间上限能有效地降低调度分析时间。同时该上限用于任务集的充分性可调度测试时具有线性时间的复杂度。这种线性上限的可调度性测试能够用于交互的系统工具设计、基于搜索的系统优化以及任务集的动态接纳新任务的设计中。并且新的调度系统模型无时间死线、抖动大小限制,适用范围更广。相关的实验也表明响应时间上限可调度性分析提高了准确调度测试的效率。     

Improved priority assignment for global fixed priority pre-emptive scheduling in multiprocessor real-time systems

This paper is an extended version of a paper that appeared in the proceedings of the IEEE Real-Time Systems Symposium 2009. This paper has been updated with respect to advances made in schedulability analysis, and contains a number of significant additional results.     

Improved response-time bounds in fixed priority scheduling with arbitrary deadlines

We consider fixed priority sporadic tasks with arbitrary deadlines to be executed upon a uni-processor platform. Efficient schedulability tests for this task model are required for both online task admission in dynamic systems and interactive design of complex embedded real-time systems. The paper derives novel continuous upper bounds on the worst-case response times which runs in linear complexity. These bounds are not comparable to the tightest existing continuous upper bound of Bini et al. (in: Proceedings of the IEEE international conference on real-time systems symposium (RTSS’15), San Antonio, 2015) and strictly tighter under some parameters configurations. Moreover, the proposed approach allows to combine various existing methods to produce the tightest known continuous response time bounds. These results are extended to be applicable to a wide range of processor and network scheduling problems, including: release jitters, blocking times and cache related preemption delay (CRPD). Response time upper bounds are also given for tasks that are scheduled pre-emptively, co-operatively with intervals where pre-emption is deferred, and non-preemptively. Lastly, the quality of the method is analyzed and various recommendations are provided by means of numerical experiments.     

On-line schedulability tests for adaptive reservations in fixed priority scheduling

Adaptive reservation is a real-time scheduling technique in which each application is associated a fraction of the computational resource (a reservation) that can be dynamically adapted to the varying requirements of the application by using appropriate feedback control algorithms. An adaptive reservation is typically implemented by using an aperiodic server (e.g. sporadic server) algorithm with fixed period and variable budget. When the feedback law demands an increase of the reservation budget, the system must run a schedulability test to check if there is enough spare bandwidth to accommodate such increase. The schedulability test must be very fast, as it may be performed at each budget update, i.e. potentially at each instance of a task; yet, it must be as efficient as possible, to maximize resource usage. In this paper, we tackle the problem of performing an efficient on-line schedulability test for adaptive resource reservations in fixed priority schedulers. In the literature, a number of algorithms have been proposed for on-line admission control in fixed priority systems. We describe four of these tests, with increasing complexity and performance. In addition, we propose a novel on-line test, called Spare-Pot algorithm, which has been specifically designed for the problem at hand, and which shows a good cost/performance ratio compared to the other tests.     

Power-aware fixed priority scheduling for sporadic tasks in hard real-time systems

In this paper, we consider the generalized power model in which the focus is the dynamic power and the static power, and we study the problem of the canonical sporadic task scheduling based on the rate-monotonic (RM) scheme. Moreover, we combine with the dynamic voltage scaling (DVS) and dynamic power management (DPM). We present a static low power sporadic tasks scheduling algorithm (SSTLPSA), assuming that each task presents its worst-case work-load to the processor at every instance. In addition, a more energy efficient approach called a dynamic low power sporadic tasks scheduling algorithm (DSTLPSA) is proposed, based on reclaiming the dynamic slack and adjusting the speed of other tasks on-the-fly in order to reduce energy consumption while still meeting the deadlines. The experimental results show that the SSTLPSA algorithm consumes 26.55–38.67% less energy than that of the RM algorithm and the DSTLPSA algorithm reduces the energy consumption up to 18.38–30.51% over the existing DVS algorithm.     

Integrating planning and scheduling

Planning and scheduling research is becoming an increasingly interesting topic in the artificial intelligence area because of its immediate application to real problems. Although the last few years have seen dramatic advances in planning systems, they have not seen the same advances in the methods of solving planning and scheduling problems. In this paper, an intuitive way of integrating independent planning and scheduling processes is presented which achieves better performance in the process of solving planning and scheduling problems. The integrated system has the advantage of obtaining a final plan that is executable and optimal. Moreover, the system discards any partial plan as soon as the plan becomes invalid, improving its performance. Experience demonstrates the validity of this system for tackling planning and scheduling problems.     

Engineering and analysis of fixed priority schedulers

Scheduling theory holds great promise as a means to a priori validate timing correctness of real-time applications. However, there currently exists a wide gap between scheduling theory and its implementation in operating system kernels running on specific hardware platforms. The implementation of any particular scheduling algorithm introduces overhead and blocking components which must be accounted for in the timing correctness validation process. This paper presents a methodology for incorporating the costs of scheduler implementation within the context of fixed priority scheduling algorithms. Both event-driven and timer-driven scheduling implementations are analyzed. We show that for the timer-driven scheduling implementations the selection of the timer interrupt rate can dramatically affect the schedulability of a task set, and we present a method for determining the optimal timer rate. We analyzed both randomly generated and two well-defined task sets and found that their schedulability can be significantly degraded by the implementation costs. Task sets that have ideal breakdown utilization over 90% may not even be schedulable when the implementation costs are considered. This work provides a first step toward bridging the gap between real-time scheduling theory and implementation realities. This gap must be bridged for any meaningful validation of timing correctness properties of real-time applications     

优先级受限系统中可调度判定方法

在通信、雷达、导航以及各种消费类电子产品等民用和军事领域,嵌入式实时调度已逐渐成为电子电气系统的控制核心。针对同优先级任务使用FIFO调度的静态优先级系统,使用反例指出给定同优先级任务初始执行顺序的前提下,Katcher可调度判定条件的必要性不成立,提出并解析证明了FP可调度的充要条件。随机实验表明,对于高利用率下任务间执行时间差异较大的情况,约有15%的可调度任务集会被Katcher条件错判为不可调度。进一步的仿真和实例分析表明,Liu、Lehoczky、Bini等提出的条件不能判定相同优先级的情况,Katcher条件的必要性不成立,论文提到的条件能够正确判定任务集的可调度性。提出方法为实时系统调度的顶层设计提供了快速离线工具。     

动态优先级作业调度算法与实现

介绍了作业调度几种基本算法及其优缺点,设计了综合几种作业调度基本算法优点的动态优先级作业调度算法,并给以方案实现,对基于微机集群的各种应用有很大的参考作用。     

关于RTOS抢占式调度及优先级反转的几点探讨

抢占式调度是RTOS的一个重要的调度策略,它保证了嵌入式系统的实时性.合理地分配任务的优先级和使用系统资源将会大大提高系统的性能.而解决优先级反转问题将保证系统共享资源的合理使用和多任务的正常运行.在对RTOS抢占式调度策略的研究的基础上,指出了什么是优先级反转,以及问题发生的原因,并给出了优先级继承和优先级封顶的解决方法.     

Evolving priority scheduling heuristics with genetic programming

This paper investigates the use of genetic programming in automated synthesis of scheduling heuristics for an arbitrary performance measure. Genetic programming is used to evolve the priority function, which determines the priority values of certain system elements (jobs, machines). The priority function is used within an appropriate meta-algorithm for a given environment, which forms the priority scheduling heuristic. The evolved solutions are compared with existing scheduling heuristics and found to perform similarly to or better than existing algorithms. We intend to show that this approach is particularly useful for combinations of scheduling environments and performance measures for which no adequate scheduling algorithms exist.     

一种基于优先级表的实时调度方法

针对单处理器实时系统动态调度问题进行了研究,分析任务的到达时间、执行时间、截止时间和空闲时间等任务属性的敏感度和影响度,提出了一种基于优先级表的调度算法PTBM,使相对截止期越小、空闲时间越大的任务优先级越高。对关于实时任务属性敏感度和影响度的结论验证和与传统的EDF、LLF和PTD算法的对比进行仿真实验,仿真结果表明基于优先级表设计的实时调度算法PTBM具有较高的调度成功率。该方法可应用于实时系统的实时任务的动态调度中。     

优先级周期性互换的实时调度算法

针对实时多任务调度时低优先级任务的延迟问题,提出了一种优先级周期性互换的静态优先级调度算法。该方法以固定的时间片为周期,对多任务系统中的某两个不同优先级的独立性任务,周期性地互换它们的优先级级别,在保证较高优先级任务的执行时间的前提下,使得较低优先级的任务有机会尽快执行,以缩短其执行过程中的延迟时间。所提方法能有效解决低优先级任务的实时性问题,从而提高实时多任务系统的整体控制性能。     

Fuzzy priority rule for job shop scheduling

Job shop scheduling uses various kinds of priority rules such as SPT, CR, COVERT, etc. Each of these rules aims at satisfying a single criterion though scheduling is a multi criteria problem. In this paper, a new approach using fuzzy logic is introduced to combine SPT, CR priority rules, and next machine's load (NML) rate the job to be processed next in order to satisfy not only a single objective but also all objectives. Fuzzy logic calculates priority value by considering SPT, CR, and NML. We named this priority rule as fuzzy priority rule (FPR). The job with the highest priority value is assigned to machine to be processed. To compare FPR with other priority rules such as SPT, EDD, etc. we run simulation. The results indicate significant improvements on mean flow time, mean tardiness, work in process (WIP), and throughput simultaneously.     

Finding conclusion stability for selecting the best effort predictor in software effort estimation

Background: Conclusion Instability in software effort estimation (SEE) refers to the inconsistent results produced by a diversity of predictors using different datasets. This is largely due to the “ranking instability” problem, which is highly related to the evaluation criteria and the subset of the data being used. Aim: To determine stable rankings of different predictors. Method: 90 predictors are used with 20 datasets and evaluated using 7 performance measures, whose results are subject to Wilcoxon rank test (95 %). These results are called the “aggregate results”. The aggregate results are challenged by a sanity check, which focuses on a single error measure (MRE) and uses a newly developed evaluation algorithm called CLUSTER. These results are called the “specific results.” Results: Aggregate results show that: (1) It is now possible to draw stable conclusions about the relative performance of SEE predictors; (2) Regression trees or analogy-based methods are the best performers. The aggregate results are also confirmed by the specific results of the sanity check. Conclusion: This study offers means to address the conclusion instability issue in SEE, which is an important finding for empirical software engineering.     

Integrating synchronization with priority into a Kronecker representation

The compositional representation of a Markov chain using Kronecker algebra, according to a compositional model representation as a superposed generalized stochastic Petri net or a stochastic automata network, has been studied for a while. In this paper we describe a Kronecker expression and associated data structures, that allows to handle nets with synchronization over activities of different levels of priority. New algorithms for these structures are provided to perform an iterative solution method of Jacobi or Gauss–Seidel type. These algorithms are implemented in the APNN Toolbox. We use this implementation in combination with GreatSPN and exercise an example that illustrates characteristics of the presented algorithms.