A new algorithm to prove the schedulability of real-time systems

In hard real-time multiprocessor systems, tasks not only have timing constraints but also often have precedence constraints caused by communication among themselves. In this paper a new algorithm to prove the schedulability of real-time systems is proposed, in which both precedence constraints and communication costs are considered and represented by offsets and modified deadlines. To obtain a tight upper bound for the worst-case response time, the concepts of local critical instant and local worst-case response time are introduced. The proposed algorithm is compared with other algorithms using test cases. The comparison shows that the proposed algorithm has improved the performances to these compared algorithms.     

A pre-run-time scheduling algorithm for object-based distributed real-time systems

The most important goal in hard real-time systems is to guarantee that all timing constraints are satisfied. Even though object-based techniques (which contain reusable software components) are used to manage the complexity in the software development process of such systems, execution efficiency may have to be sacrificed, due to the large number of procedure calls and contention for accessing software components. These issues are addressed by the following parallelizing techniques: (a) converting potentially inefficient procedure calls to a source of concurrency via asynchronous remote procedure calls (ARPC) (b) replicating (or cloning) software components to reduce the contention. The existing object-based scheduling algorithms construct an initial schedule and apply incremental parallelization techniques to modify the initial schedule till a feasible schedule is generated. But these algorithms are applicable for scheduling only multiple independent tasks. This paper describes a pre-run-time scheduling algorithm for a set of periodic object-based tasks having precedence constraints among them. The algorithm allocates the components of object-based periodic real-time tasks to the sites of a distributed system based on a clustering heuristic which takes into account the ARPC parallelism and load balancing, and schedules them on respective sites. The algorithm also finds a schedule for communication channel(s). Further, it clones the components of object-based periodic tasks, if contention occurs in accessing them. In addition to the above (periodicity and precedence) constraints, the tasks handled by our algorithm can have resource constraints among them. The experimental evaluation of the algorithm shows that the combination of the proposed clustering heuristic and cloning enhances schedulability.     

一种面向部分可重构FPGA的混合实时调度算法

在CPU/FPGA平台上运行的实时任务通常由软/硬件子任务组成并存在优先约束关系。提出了一种软/硬件混合实时任务调度算法。在截止期限错失时刻,通过分析系统的运行情况,推导出实时任务可调度的充分条件。每个实时任务的硬件子任务分成多组,每组硬件子任务重叠配置到FPGA上。通过手工布局硬件子任务端口和总线端口,使得硬件子任务可动态的连接到系统总线上。实验表明,该算法能够满足任务的实时性,充分利用FPGA资源。     

OPC实时任务系统动态调度算法的研究与设计

本文基于已有的OPCServer实时任务模型,设计了处理混合任务集的动态调度算法(基于截止期优先)和实现方式。该算法实现了对混合任集可调度性的判断,可以完成有硬实时性要求的非周期性任务和周期性任务的调度,并给出了相应的调度结果。     

端到端时间约束的实时任务动态调度算法

在单处理机系统中,由于计算高优先级任务抢占的时间相对比较简单,所以单处理机调度理论取得了长足的进步.提出一个端到端时间约束的实时任务调度算法,当实时任务到达系统时,算法为任务的每个子任务在相应的处理机上预约一定的计算资源,把端到端的多处理机调度问题转换成单处理机调度问题,从而可以利用单处理机调度理论判定实时任务的可调度性.实验表明,该算法明显地提高了CPU利用率和任务接收率.     

满足偏序约束的在线调度

具备偏序关系的实时调度要求调度算法产生的执行序列既要满足任务的实时约束,又要满足任务间执行的偏序约束。基于并行拓扑排序,提出一种新的在线调度算法,该算法通过同时考察任务间执行的串行性和并行性来进行优先级设置,能够处理释放时间任意的任务集。给出该算法的原理和设计,并通过示例分析和比较对算法进行验证。     

A genetic algorithm for multiprocessor scheduling

The problem of multiprocessor scheduling can be stated as finding a schedule for a general task graph to be executed on a multiprocessor system so that the schedule length can be minimized. This scheduling problem is known to be NP-hard, and methods based on heuristic search have been proposed to obtain optimal and suboptimal solutions. Genetic algorithms have recently received much attention as a class of robust stochastic search algorithms for various optimization problems. In this paper, an efficient method based on genetic algorithms is developed to solve the multiprocessor scheduling problem. The representation of the search node is based on the order of the tasks being executed in each individual processor. The genetic operator proposed is based on the precedence relations between the tasks in the task graph. Simulation results comparing the proposed genetic algorithm, the list scheduling algorithm, and the optimal schedule using random task graphs, and a robot inverse dynamics computational task graph are presented     

Assignment and scheduling communicating periodic tasks indistributed real-time systems

Presents an optimal solution to the problem of allocating communicating periodic tasks to heterogeneous processing nodes (PNs) in a distributed real-time system. The solution is optimal in the sense of minimizing the maximum normalized task response time, called the system hazard, subject to the precedence constraints resulting from intercommunication among the tasks to be allocated. Minimization of the system hazard ensures that the solution algorithm allocates tasks so as to meet all task deadlines under an optimal schedule, whenever such an allocation exists. The task system is modeled with a task graph (TG), in which computation and communication modules, communication delays and intertask precedence constraints are clearly described. Tasks described by this TG are assigned to PNs by using a branch-and-bound (B&B) search algorithm. The algorithm traverses a search tree whose leaves correspond to potential solutions to the task allocation problem. We use a bounding method that prunes, in polynomial time, nonleaf vertices that cannot lead to an optimal solution, while ensuring that the search path leading to an optimal solution will never be pruned. For each generated leaf vertex, we compute the exact cost using the algorithm developed by Peng and Shin (1993). The lowest-cost leaf vertex (one with the least system hazard) represents an optimal task allocation. Computational experiences and examples are provided to demonstrate the concept, utility and power of the proposed approach     

Static scheduling of directed acyclic data flow graphs onto multiprocessors using particle swarm optimization

An efficient method based on particle swarm optimization (PSO) is developed to solve the Multiprocessor Task Scheduling Problem (MPTSP). To efficiently execute parallelized programs on a multiprocessor environment, a scheduling problem must be solved to determine the assignment of tasks to the processors, the execution order of the tasks, and the starting time of each task, such that some optimality criteria are met. The scheduling problem is known as an NP-complete problem even when the target processors are fully connected and no communication delay is considered among the tasks in the task graph. The complexity of the scheduling problem depends on the number of tasks (N), the number of processors (M), the task processing time and the precedence constraints. The Directed Acyclic Graph (DAG) was exploited to represent the tasks and their precedence constraints. The proposed algorithm was compared with the Genetic Algorithm (GA) and the Duplication Scheduling Heuristic (DSH). We also provide a systematic investigation on the effect of varying problem settings. The results show that the proposed algorithm could not outperform the DSH while it could outperform the GA in some cases.     

On Schedulability Analysis of AADL Architecture with Storage Resource Constraint

Embedded systems have been widely applied in real-time automatic control systems, and most of these systems are safety-critical, for example, the engine control systems in an automobile and the avionics in an airplane. It is very important to verify the schedulability of such a real-time embedded system in its early design stages, so as to avoid unexpected loss for the debugging of architecture design problems. However, it has been proved to be a tough challenge to evaluate the schedulability of a Preemptive-Scheduling Real-Time (PSRT) system, especially when the constraints of system resources are taken into consideration. The cache memory built inside the processor is an exclusive-accessing resource shared by all the tasks deployed on the processor. In addition, the Cache-Related Preemption Delay (CRPD) caused by preemptive task scheduling will bring extra time to the execution time for all the tasks. Thus, the CRPD should be taken into consideration when the Worst-Case Execution Time (WCET) of tasks is estimated in a real-time system. A model-based evaluation and verification method of architecture schedulability, which is designed for priority-based PSRT systems, is proposed in this study to make cache resource constrained and CRPD related schedulability evaluation based on the AADL system architecture model. In the first step, the study enhances the property set of AADL storage elements to make it compatible with cache memory properties in a system architecture model. Secondly, the study proposes a set of algorithms to estimate the CRPDs of a task before it is completed; run system schedule simulation and construct the schedule sequence with the constraint of cache resources and CRPDs involved; and make WCET estimation of the tasks in such a CRPD considered, preemptive-scheduling execution sequence. Finally, the methods mentioned above are implemented within a prototype software toolkit, which is designed to make evaluation and verification of system schedulability within CRPD constraints. The toolkit is tested with a use case of aircraft airborne open-architecture intelligent information system. The result shows that, compared with the schedule sequence constructed without cache memory resource constraints, the WCET estimated for most tasks is extended, and the sequence order is changed. In some extreme cases, when CRPD is taken into consideration, some tasks are evaluated to be incompletable. The test shows that the method and algorithms proposed in this study are feasible.     

Dynamic scheduling of real-time tasks under precedence constraints

While scheduling theory has been developed over a long period of time, it is important to note that most results concern problems with static characteristics. However, a real-time system is dynamic and requires on-line and adaptive scheduling strategies. So, an important aspect of real-time systems research is to devise methods flexible enough to react to a dynamic change of processor load and to attempt to schedule all the tasks judiciously.In this paper, we are particularly concerned with the problem of scheduling tasks which are of two kinds: periodic and sporadic, on a monoprocessor machine. Periodic tasks are independent, run cyclically and their characteristics are known in advance. In addition, we allow for the unpredictable occurrence of aperiodic task groups, with timing and precedence constraints. Clearly, the main problem is to devise a schedulability test that makes it possible to decide whether a new occurring group can be accepted, without upsetting the tight timing behavior requirements.We present an optimal acceptance test which returns a decision on the basis of the current state of processor load and by considering tasks to be scheduled according to the well known preemptive algorithm Earliest Deadline. The acceptance algorithm and a complexity analysis are presented.     

An efficient approach for the multiprocessor non-preemptive strictly periodic task scheduling problem

Strict periodicity constraint is of great importance since it concerns some hard real-time systems where missing deadlines leads to catastrophic situations. However, the problem of schedulability analysis for non-preemptive strictly periodic tasks on a multiprocessor platform is even more intractable than the one with the common periodicity. In order to implement such systems, designers need effective tools based on fast and near-optimal solutions.This paper presents a schedulability analysis which results mainly in a, two versions, task assignment and start-time calculation algorithm. The first one targets the harmonic task periods case while the second one targets the non-harmonic task periods case. Each version is based on a sufficient uniprocessor schedulability test. In addition, for the non-harmonic case which is the most intractable, the uniprocessor sufficient schedulability test uses the strictly periodic task utilization factor. This factor stands for the fraction of time spent to execute a task while its strict periodicity and the ones of the already scheduled tasks are met. As a result, an efficient and easily implementable scheduling algorithm is proposed which begins by assigning tasks to processors then attributes a start-time to every task in such a way that strict periodicity and deadline constraints are met. The effectiveness of the proposed scheduling algorithm, in both versions, has been shown by a performance evaluation and comparisons with an optimal and a similar suboptimal solution.     

Task scheduling with precedence constraints to minimize the total completion time

The authors study the problem of scheduling a set of tasks with known execution times and arbitrary precedence constraints to computing systems. The objective function used to measure the performance of a schedule in this paper is the sum of completion times of all tasks, which is called total completion time. Finding the minimum total completion time of tasks with precedence constraints on the uniprocessor system is known to be NP-complete, let alone on the multiprocessor system (Garey and Johnson 1979) Based on the well-known A? algorithm proposed in the field of artificial intelligence (Nilson 1980) two algorithms are developed to solve efficiently the scheduling problems on the uniprocessor system and multiprocessor system. Some evaluation functions are proposed to accelerate the search of an optimal schedule. A table named the backwards range-limited table is used to assist the computation of the evaluation function. Experimental results show that the proposed approaches can achieve the optimal schedule with greatly reduced search tree size, especially when bounding rules are applied.     

FF现场总线系统中实时任务的建模与调度

本文研究了单网段 FF现场总线系统中具有时间约束和次序约束的实时任务，即 功能块任务和通信任务的建模与调度．首先，将功能块任务和通信任务等视为相同的任务， 在只考虑任务间次序约束的情况下，提出了基于紧凑模式的任务模型，以保证每个作业被尽 可能早地完成．其次，考虑单网段通信任务共享一个传输介质而引起的通信超时，提出了基 于作业速率单调优先级算法的扩展紧凑模式的任务调度算法，以满足实时任务的时间约束 和次序约束．最后，通过一个应用实例来描述实时任务的调度过程．     

动态可重构片上系统的任务在线调度算法

针对动态可重构系统中为新到达任务安排任务启动时间和放置位置的问题,提出一种基于顶点链表的Look-aheadest算法。将任务调度的时间作为时间维,通过已到达任务与已放置任务在三维空间的邻接面构建代价函数,获取具有最大代价函数值的放置位置和启动时间,使硬件任务放置更为紧凑,提高调度成功率。仿真结果表明,在可接受的运行开销内,该算法能有效提高任务接受率。     

面向AADL模型的存储资源约束可调度性分析

嵌入式实时系统在安全关键领域变得越来越重要,其广泛应用于航空航天、汽车电子等具有严格时间约束的实时系统中.随着嵌入式系统的复杂度越来越高,在系统开发的早期设计阶段就需要对其可调度性进行分析评估.系统中的存储资源会对可调度性产生一定影响,在抢占式实时嵌入式系统引入缓存后,任务的最坏执行时间可能发生变化.因此,分析缓存相关抢占延迟对实时嵌入式系统的可调度性影响一直以来是困扰大规模复杂系统架构设计的一个技术难题.本文提出了一种面向软件架构级别、基于抢占调度序列的缓存相关抢占延迟计算方法,用来分析缓存相关抢占延迟约束下AADL （架构分析和设计语言）模型的可调度性.论文扩展了AADL关于存储资源架构设计的模型元素,来支持对缓存属性进行建模,提出了一种基于模型构件进行抢占序列排序、缓存相关抢占延迟时间计算和被抢占任务最坏执行时间的估算方法,来对系统架构各功能构件在共享系统存储资源下系统的可调度性进行分析.论文还实现了分析缓存相关抢占延迟约束下的系统任务可调度性分析工具原型,并以某型飞机机载开放式智能信息系统为例,在航空电子系统架构设计中进行尝试,验证了该方法的在复杂系统设计中的对实时性分析的可行性.     

一种能量收集嵌入式系统自适应调度算法

能量收集嵌入式系统(energy harvesting embedded system,简称EHES)的任务调度算法需要考虑能量收集单元的能量输出、能量存储单元的能量水平和能量消耗单元的能耗.实时任务在满足能量约束的条件下,才可能满足时间约束.在这个背景下,传统固定优先级调度算法不再适用于EHES.提出一种基于分组的自适应任务调度算法,它能根据能量收集单元由于能量输出的不确定性而造成的非能量约束情况和能量约束情况,自适应地选择任务调度算法.在非能量约束的情况下,减少任务抢占次数,增强任务的可调度性;在能量约束情况下,减少电池模式切换次数,提高能量存储单元的平均能量水平,从而降低系统能量约束.在一个可进行大范围任务集合仿真的实验环境下对提出的算法进行验证,并将基于分组的自适应调度算法与现有的两个经典算法进行了对比.     

Timing analysis for fixed-priority scheduling of hard real-timesystems

This paper presents a timing analysis for a quite general hard real-time periodic task set on a uniprocessor using fixed-priority methods. Periodic tasks are composed of serially executed subtasks, where each subtask is characterized by an execution time, a fixed priority and a deadline. A method for determining the schedulability of each task and subtask is presented along with its theoretical underpinnings. This method can be used to analyze the schedulability of any task set on a uniprocessor whose priority structure can be modeled as serially executed subtasks, which can lead to a very complex priority structure. Important examples include task sets that involve interrupts, certain synchronization protocols, certain precedence constraints, nonpreemptible sections, and some message-passing systems. The method is illustrated by a robotics example     

Combined task and message scheduling in distributed real-timesystems

The paper presents an algorithm for offline scheduling of communicating tasks with precedence and exclusion constraints in distributed hard real time systems. Tasks are assumed to communicate via message passing based on a time bounded communication paradigm, such as the real time channel (D.D. Kandlur et al., 1994). The algorithm uses a branch-and-bound (B & B) technique to search for a task schedule by minimizing maximum task lateness (defined as the difference between task completion time and task deadline), and exploits the interplay between task and message scheduling to improve the quality of solution. It generates a complete schedule at each vertex in the search tree, and can be made to yield a feasible schedule (found before reaching an optimal solution), or proceed until an optimal task schedule is found. We have conducted an extensive simulation study to evaluate the performance of the proposed algorithm. The algorithm is shown to scale well with respect to system size and degree of intertask interactions. It also offers good performance for workloads with a wide range of CPU utilizations and application concurrency. For larger systems and higher loads, we introduce a greedy heuristic that is faster but has no optimality properties. We have also extended the algorithm to a more general resource-constraint model, thus widening its application domain     

On a parallel machine scheduling problem with precedence constraints

We characterize a nontrivial special case with a polynomial-time algorithm for a well-known parallel machine scheduling problem with precedence constraints, with a fixed number of machines, and with tasks of unit length. The special case is related to instances with given maximum path length and maximum degree of the task precedence graph. The method is based on the observation that the number of tasks is either small and bounded by a constant depending on the maximum path length and maximum degree, or alternatively, the number of tasks is large, giving a “dense” schedule.