周期性任务调度的装箱算法

针对基于时间触发的CAN控制系统,给出了确定周期性任务表中的基本周期的两种策略,提出了构造周期性任务调度表的下次适应、降序下次适应、最佳适应和降序最佳适应四种算法,分析了这四种不同算法的时间复杂度和最坏渐近性能比,最后对不同规模下的四种算法进行了仿真比较,结果表明文中给出的四种算法效果均优于经典的一维装箱算法。     

Preference-oriented fixed-priority scheduling for periodic real-time tasks

Traditionally, real-time scheduling algorithms prioritize tasks solely based on their timing parameters and cannot effectively handle tasks that have different execution preferences. In this paper, for a set of periodic real-time tasks running on a single processor, where some tasks are preferably executed as soon as possible (ASAP) and others as late as possible (ALAP), we investigate Preference-Oriented Fixed-Priority (POFP) scheduling techniques. First, based on Audsley’s Optimal Priority Assignment (OPA), we study a Preference Priority Assignment (PPA) scheme that attempts to assign ALAP (ASAP) tasks lower (higher) priorities, whenever possible. Then, by considering the non-work-conserving strategy, we exploit the promotion times of ALAP tasks and devise an online dual-queue based POFP scheduling algorithm. Basically, with the objective of fulfilling the execution preferences of all tasks, the POFP scheduler retains ALAP tasks in the delay queue until their promotion times while putting ASAP tasks into the ready queue right after their arrivals. In addition, to further expedite (delay) the executions of ASAP (ALAP) tasks using system slack, runtime techniques based on dummy and wrapper tasks are investigated. The proposed schemes are evaluated through extensive simulations. The results show that, compared to the classical fixed-priority Rate Monotonic Scheduling (RMS) algorithm, the proposed priority assignment scheme and POFP scheduler can achieve significant improvement in terms of fulfilling the execution preferences of both ASAP and ALAP tasks, which can be further enhanced at runtime with the wrapper-task based slack management technique.     

MVB周期信息的实时调度

多功能车辆总线MVB网络对周期信息的通信提出了很高的实时要求,其通信的实时调度主要由MVB总线管理设备利用实时调度表来完成。在分析一般现场总线周期信息实时调度的基础上,结合MVB周期信息的通信特点,提出了采用同步RM调度算法来建立MVB实时调度表的原理与方法;并进一步提出了采用基于任务响应时间的方法对该调度算法进行可调度性分析,给出了一种有效算法,用以实现对调度表的有效性判断;最后通过MVB周期信息实例阐述了所提出的实时调度算法及其可调度性分析方法的具体应用,为实际MVB网络的应用研究提供了理论指导。     

On periodic resource scheduling for continuous-media databases

The Enhanced Pay-Per-View (EPPV) model for providing continuous-media services associates with each continuous-media clip a display frequency that depends on the clip's popularity. The aim is to increase the number of clients that can be serviced concurrently beyond the capacity limitations of available resources, while guaranteeing a constraint on the response time. This is achieved by sharing periodic continuous-media streams among multiple clients. The EPPV model offers a number of advantages over other data-sharing schemes (e.g., batching), which make it more attractive to large-scale service providers. In this paper, we provide a comprehensive study of the resource-scheduling problems associated with supporting EPPV for continuous-media clips with (possibly) different display rates, frequencies, and lengths. Our main objective is to maximize the amount of disk bandwidth that is effectively scheduled under the given data layout and storage constraints. Our formulation gives rise to -hard combinatorial optimization problems that fall within the realm of hard real-time scheduling theory. Given the intractability of the problems, we propose novel heuristic solutions with polynomial-time complexity. We also present preliminary experimental results for the average case behavior of the proposed scheduling schemes and examine how they compare to each other under different workloads. A major contribution of our work is the introduction of a robust scheduling framework that, we believe, can provide solutions for a variety of realistic EPPV resource-scheduling scenarios, as well as any scheduling problem involving regular, periodic use of a shared resource. Based on this framework, we propose various interesting research directions for extending the results presented in this paper. Received June 9, 1998 / Accepted October 13, 1998     

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。     

Adaptive general perfectly periodic scheduling

We propose an adaptive algorithm Adaptmin to create perfectly periodic schedules. A perfectly periodic schedule schedules a client regularly after a predefined amount of time known as the period of the client. The periodicity of such schedules can be used to save battery life of nodes in a wireless network. The quality of a perfectly periodic schedule is a function of the ratio between the granted and requested periods. We find a worst case performance bound on the quality of schedules produced by Adaptmin. We compare our algorithm to previously proposed algorithm A in [Z. Brakerski, A. Nisgav, B. Patt-Shamir, General perfectly periodic scheduling, in: Proc. 21st Annual Symp. on Principles of Distributed Computing, 2002, pp. 163-172], and show families of input instances where either Adaptmin does no worse than A, or always outperforms A. The better performance of the proposed algorithm is also confirmed by simulations results for randomly generated input instances. Adaptmin produces 25% more efficient schedules as compared to A in our experiments. We also propose a variant of Adaptmin which is computationally much less demanding compared to A, but is very close to Adaptmin in terms of efficiency. Finally, we compare our algorithms to exponential-time optimal scheduling. Our simulation results indicate that the performance of the proposed algorithms is close to that of optimal scheduling.     

Complexity results for the basic residency scheduling problem

Upon graduation from medical school, medical students join residency programs to complete their clinical training and fulfill specialty board certification requirements. During residency, they are assigned several years of clinical rotations, where they work under the supervision of physician faculty in a variety of different settings, to ensure that they gain the requisite training prior to beginning independent practice. These rotations typically last a short period of time, and the problem of determining a schedule for all the residents in a program can be quite tedious. In this paper, a basic residency scheduling problem that produces a 1-year schedule is defined, and a proof of NP-completeness is presented. Furthermore, a specific model of the residency scheduling program for the internal medicine residency program at the University of Illinois College of Medicine at Urbana-Champaign is studied. Finally, a method for determining alternate optima is presented.     

An optimal scheduling algorithm for periodic testing of systems

The problem of optimizing the periodicity and volume of testing in a system is considered. The solution is obtained by dynamic programming. A numerical example is solved.Translated from Kibernetika, No. 2, pp. 86–90, March–April, 1991.     

A new algorithm for scheduling periodic, real-time tasks

We consider the problem of preemptively scheduling a set of periodic, real-time tasks on a multiprocessor computer system. We give a new scheduling algorithm, the so-called Slack-Time Algorithm, and show that it is more effective than the known Deadline Algorithm. We also give an (exponential-time) algorithm to decide if a task system is schedulable by the Slack-Time or the Deadline Algorithm. The same algorithm can also be used to decide if a task system is schedulable by any given fixed-priority scheduling algorithm. This resolves an open question posed by Leung and Whitehead. Finally, it is shown that the problem of deciding if a task system is schedulable by the Slack-Time, the Deadline, or any given fixed-priority scheduling algorithm is co-NP-hard for each fixedm.     

A new algorithm for scheduling periodic,real-time tasks

Algorithmica - We consider the problem of preemptively scheduling a set of periodic, real-time tasks on a multiprocessor computer system. We give a new scheduling algorithm, the so-called...     

Modified rate-monotonic algorithm for scheduling periodic jobs withdeferred deadlines

The deadline of a request is the time instant at which its execution must complete. The deadline of the request in any period of a job with deferred deadline is some time instant after the end of the period. The authors describe a semi-static priority-driven algorithm for scheduling periodic jobs with deferred deadlines: each job is assigned two priorities, the higher one for old requests and the lower one for the current request. This algorithm is called the modified rate-monotonic algorithm and is based on the well-known rate-monotonic algorithm. It is shown that the modified rate-monotonic algorithm is optimal when the deadline of every job is deferred by max (1, γ-1) periods or more, where γ is the ratio between the longest period and the shortest period. When the deadline of each job is deferred by one period of the job, any set of n independent jobs whose total utilization is equal to or less than [1+n(2¹n/-1)]/2 can be feasibly scheduled by this algorithm. This bound approaches 0.845 when n approaches infinity     

Real-time load balancing scheduling algorithm for periodic simulation models

A scheduling algorithm is crucial for real-time simulations because it guarantees that each model meets its deadline. Traditional online real-time scheduling algorithms such as Earliest Deadline First (EDF) introduce a high overhead when scheduling a large number of models. In this paper, a new algorithm called time-stepped load balancing (TLS) is proposed to address the real-time execution of a model set in a time-stepped simulation. A load balancing schedule table is generated before a simulation and rebalanced at runtime to dynamically schedule the changed model set. This table is organized by the execution periods of the models and balanced according to the load of each time step. Moreover, the slack time is distributed evenly among the steps to improve the real-time reliability. An extension to the algorithm for a multi-core environment is further studied to address those models with long execution times. Experimental results show that our scheduling algorithm outperforms the classical EDF approach. The highest performance improvement of TLS over EDF reaches 3–4% in terms of saving processor resources, and the jitter is about 4 times less when 90 entities are employed in a typical tank combat simulation scenario.     

Strictly periodic scheduling in IMA-based architectures

The avionic industry has recently adopted the Integrated Modular Avionics (IMA). Such architectures allow the execution of avionic functions on a shared computing platform while avoiding any interference between them. This is done through hard memory and temporal segregation constraints. Although IMA reduces the weight and the power consumption and shortens the design-cycle times, it gives rise to a complex multiprocessor scheduling problem. One of the key difficulties of this problem is related to the strict periodicity of tasks, which means that the time separating two successive executions of the same task is strictly equal to the associated period. In order to help the system designer in producing a proper schedule, an exact formulation based on Integer Linear Programming and a heuristic inspired from Game Theory are proposed. To enhance the solution quality of the heuristic, a?multi-start method, which gives some probabilistic guarantees on the optimality of the solutions, is also introduced.     

A new fair scheduling algorithm for periodic tasks on multiprocessors

We present a new scheduling algorithm, called PL that is work-conserving and in terms of schedulability, optimal on multiprocessors for a synchronous periodic task set. The PL algorithm is a laxity based algorithm and ensures execution of a task with approximate proportional fairness at each task's period. Existing optimal algorithms on multiprocessors may cause excessive scheduling decisions and preemptions or may not be applied in a discrete environment. The proposed algorithm can be applied in a discrete environment and reduce the number of scheduling decisions and preemptions compared with a Pfair algorithm.     

Allocation and scheduling of precedence-related periodic tasks

This paper discusses a static algorithm for allocating and scheduling components of periodic tasks across sites in distributed systems. Besides dealing with the periodicity constraints, (which have been the sole concern of many previous algorithms), this algorithm handles precedence, communication, as well as replication requirements of subtasks of the tasks. The algorithm determines the allocation of subtasks of periodic tasks to sites, the scheduled start times of subtasks allocated to a site, and the schedule for communication along the communication channel(s). Simulation results show that the heuristics and search techniques incorporated in the algorithm are very effective     

Single-machine scheduling with periodic and flexible periodic maintenance to minimize maximum tardiness

This paper considers a single-machine scheduling problem with several maintenances periods. Specifically, two situations are investigated. In the first one, maintenance periods are periodically fixed: maintenance is required after a periodic time interval. In the second one, the maintenance is not fixed but the maximum continuous working time of the machine which is allowed is determined. The objective is to minimize the maximum tardiness. These problems are known to be strongly NP-hard. We propose some dominance properties and an efficient heuristic. Branch-and-bound algorithms, in which the heuristics, the lower bounds and the dominance properties are incorporated, are proposed and tested computationally.     

Line search method for solving a non-preemptive strictly periodic scheduling problem

We study a non-preemptive strictly periodic scheduling problem. This problem arises for example in the avionic field where a set of \(N\) periodic tasks (measure of a sensor, data presentation, etc.) has to be scheduled on \(P\) processors distributed on the plane. In this article, we consider an existing heuristic which is based on the notion of equilibrium. Following a game theory analogy, each task tries successively to optimize its own schedule and, therefore, to produce the best response, given the other schedules. This iterative process continues until an equilibrium is reached. We present a new method to compute the best response which significantly improves the previously proposed heuristic, and compares favorably with MILP solutions.     

Single-machine scheduling with periodic maintenance to minimize makespan

We consider a single-machine scheduling problem with periodic maintenance activities. Although the scheduling problem with maintenance has attracted researchers’ attention, most of past studies considered only one maintenance period. In this research several maintenance periods are considered where each maintenance activity is scheduled after a periodic time interval. The objective is to find a schedule that minimizes the makespan, subject to periodic maintenance and nonresumable jobs. We first prove that the worst-case ratio of the classical LPT   algorithm is 2. Then we show that there is no polynomial time approximation algorithm with a worst-case ratio less than 2 unless P=NP$P=\text{<italic>NP</italic>}$, which implies that the LPT algorithm is the best possible.     

Deadline-based scheduling of periodic task systems on multiprocessors

We consider the problem of scheduling periodic task systems on multiprocessors and present a deadline-based scheduling algorithm for solving this problem. We show that our algorithm successfully schedules on m processors any periodic task system with utilization at most m²/(2m−1).