非固定双头镜像磁盘实时调度算法的研究

文章给出一个实时非固定双头镜像磁盘系统的形式化模型.该磁盘模型中的每个双头磁盘都有两个相互独立的磁臂,能够独立地完成寻找磁道过程.针对该磁盘系统,文章研究了3种实时调度算法.模拟实验表明,“忽略超截止期调度算法”的性能最好,因为它忽略了对超截止期限实时请求的处理.文章同时分析了固定双头镜像磁盘与非固定双头镜像磁盘之间的性能差别.实验结果表明,由于非固定双头磁盘的两个磁头可以独立寻找磁道,因此非固定双头镜像磁盘的性能比固定双头镜像磁盘的性能要好.     

A non-preemptive scheduling algorithm for soft real-time systems

Real-time systems are often designed using preemptive scheduling and worst-case execution time estimates to guarantee the execution of high priority tasks. There is, however, an interest in exploring non-preemptive scheduling models for real-time systems, particularly for soft real-time multimedia applications. In this paper, we propose a new algorithm that uses multiple scheduling strategies for efficient non-preemptive scheduling of tasks. Our goal is to improve the success ratio of the well-known Earliest Deadline First (EDF) approach when the load on the system is very high and to improve the overall performance in both underloaded and overloaded conditions. Our approach, known as group-EDF (gEDF) is based on dynamic grouping of tasks with deadlines that are very close to each other, and using Shortest Job First (SJF) technique to schedule tasks within the group. We will present results comparing gEDF with other real-time algorithms including, EDF, Best-effort, and Guarantee, by using randomly generated tasks with varying execution times, release times, deadlines and tolerance to missing deadlines, under varying workloads. We believe that grouping tasks dynamically with similar deadlines and utilizing a secondary criteria, such as minimizing the total execution time (or other metrics such as power or resource availability) for scheduling tasks within a group, can lead to new and more efficient real-time scheduling algorithms.     

多媒体服务器混合磁盘调度策略

基于多媒体服务器的性能要求，提出了一种自适应的混合磁盘调度策略DRT-window．它既能满足实时请求对实时性的要求，根据实时请求的截止期动态选择窗口大小；又能在其松弛度内尽努力(best-effort)地服务非实时请求，从而减少非实时请求的响应时间。DRT-window采用了两级层次调度方案：第一层为不同类型的请求采用各自适合的调度策略；第二层为混合请求调度嚣，混合调度第一层中的不同类型的请求。通过性能比较和理论证明，表明此混合磁盘调度策略能在保证实时请求无抖动执行的同时，尽量地减少非实时请求的响应时间。     

Efficient scheduling algorithms for real-time multiprocessorsystems

Efficient scheduling algorithms based on heuristic functions are developed for scheduling a set of tasks on a multiprocessor system. The tasks are characterized by worst-case computation times, deadlines, and resources requirements. Starting with an empty partial schedule, each step of the search extends the current partial schedule by including one of the tasks yet to be scheduled. The heuristic functions used in the algorithm actively direct the search for a feasible schedule, i.e. they help choose the task that extends the current partial schedule. Two scheduling algorithms are evaluated by simulation. To extend the current partial schedule, one of the algorithms considers, at each step of the search, all the tasks that are yet to be scheduled as candidates. The second focuses its attention on a small subset of tasks with the shortest deadlines. The second algorithm is shown to be very effective when the maximum allowable scheduling overhead is fixed. This algorithm is hence appropriate for dynamic scheduling in real-time systems     

New Algorithms for Resource Reclaiming from Precedence Constrained Tasks in Multiprocessor Real-Time Systems

The scheduling of tasks in multiprocessor real-time systems has attracted many researchers in the recent past. Tasks in these systems have deadlines to be met, and most of the real-time scheduling algorithms use worst case computation times to schedule these tasks. Many resources will be left unused if the tasks are dispatched purely based on the schedule produced by these scheduling algorithms, since most of the tasks will take less time to execute than their respective worst case computation times. Resource reclaiming refers to the problem of reclaiming the resources left unused by a real-time task when it takes less time to execute than its worst case computation time. In this paper, we propose two algorithms to reclaim these resources from real-time tasks that are constrained by precedence relations and resource requirements, in shared memory multiprocessor systems. We introduce a notion called a restriction vector for each task which captures its resource and precedence constraints with other tasks. This will help not only in the efficient implementation of the algorithms, but also in obtaining an improvement in performance over the reclaiming algorithms proposed in earlier work [[2]]. We compare our resource reclaiming algorithms with the earlier algorithms and, by experimental studies, show that they reclaim more resources, thereby increasing the guarantee ratio (the ratio of the number of tasks guaranteed to meet their deadlines to the number of tasks that have arrived), which is the basic requirement of any resource reclaiming algorithm. From our simulation studies, we demonstrate that complex reclaiming algorithms with high reclaiming overheads do not lead to an improvement in the guarantee ratio.     

双头镜像磁盘的实时调度算法及性能评价

本文对双头镜像磁盘系统模型进行实时扩展,并提出了三种实时调度算法：最早截止期优先算法（ＥＤＦ）,可满足的最早截止期优先算法（Ｆ－ＥＤＦ）和忽视超时限请求算法（ＩＧＭ－ＥＤＦ）．这三种算法充分考虑了Ｉ／Ｏ请求的截止期限,使双头镜像磁盘系统能更好地满足实时需求．在进行了性能模拟后,发现实时调度算法比非实时算法能更好地满足实时Ｉ／Ｏ请求的时限要求．三种实时调度算法中,适用于硬实时应用的ＩＧＭ－ＥＤＦ的性能最好,Ｆ－ＥＤＦ算法的性能次之,它适用于软实时环境．     

A genetic based disk scheduling method to decrease makespan and missed tasks

Disk scheduling is an operating system process to service disk requests. It has an important role in QOS guarantee of soft real-time environments such as video-on-demand and multimedia servers. Since now, some disk scheduling algorithms have been proposed to schedule disk requests in an optimized manner. Most of these methods try to minimize makespan by decreasing the number of disk head seeks as one of the slowest operations in modern computers and crucial for system performance because it usually takes some milli-seconds. In this paper, we propose a new disk scheduling method based on genetic algorithm that considers makespan and number of missed tasks simultaneously. In the proposed method, a new coding scheme is presented which employs simple GA procedures such as crossover and mutation and a penalty function in fitness. To get the best performance of the proposed method, its parameters such as number of chromosomes in initial population, mutation, and crossover probabilities, etc have been adjusted by applying it on some sample problems. The algorithm has been tested on several problems and its results were compared with well-known related methods. Experimental results showed that the proposed method worked very well and excelled most related works in terms of miss ratio and average seeks.     

Disk scheduling in video editing systems

Modern video servers support both video-on-demand and nonlinear editing applications. Video-on-demand servers enable the user to view video clips or movies from a video database, while nonlinear editing systems enable the user to manipulate the content of the video database. Applications such as video and news editing systems require that the underlying storage server be able to concurrently record live broadcast information, modify prerecorded data, and broadcast an authored presentation. A multimedia storage server that efficiently supports such a diverse group of activities constitutes the focus of this study. A novel real-time disk scheduling algorithm is presented that treats both read and write requests in a homogeneous manner in order to ensure that their deadlines are met. Due to real-time demands of movie viewing, read requests have to be fulfilled within certain deadlines; otherwise, they are considered lost. Since the data to be written into disk is stored in main memory buffers, write requests can be postponed until critical read requests are processed. However, write requests still have to be processed within reasonable delays and without the possibility of indefinite postponement. This is due to the physical constraint of the limited size of the main memory write buffers. The new algorithm schedules both read and write requests appropriately, to minimize the amount of disk reads that do not meet their presentation deadlines, and to avoid indefinite postponement and large buffer sizes in the case of disk writes. Simulation results demonstrate that the proposed algorithm offers low violations of read deadlines, reduces waiting time for lower priority disk requests, and improves the throughput of the storage server by enhancing the utilization of available disk bandwidth     

A New Strategy for Improving the Effectiveness of Resource Reclaiming Algorithms in Multiprocessor Real-Time Systems

The scheduling of tasks in multiprocessor real-time systems has attracted the attention of many researchers in the recent past. Tasks in such systems have deadlines to be met, and most real-time scheduling algorithms use worst case computation times to schedule these tasks. Many resources will be left unused if the tasks are dispatched purely based on the schedule produced by these scheduling algorithms, since most of the tasks will take less time to execute than their respective worst case computation times. Resource reclaiming refers to the problem of reclaiming the resources left unused by a real-time task when it takes less time to execute than its worst case computation time. Several resource reclaiming algorithms such as Basic, Early Start, and RV algorithms have been proposed in the recent past. But these pay very little attention to the strategy by which the scheduler can better utilize the benefits of reclaimed resources. In this paper, we propose an esti- mation strategy which can be used along with a particular class of resource reclaiming algorithms (such as Early Start and RV algorithms) by which the scheduler can estimate the minimum time by which any scheduled but unexecuted task will start or finish early, based solely on the start and finish times of tasks that have started or finished execution. We then propose an approach by which dynamic scheduling strategies, which append or reschedule new tasks into the schedules, can use this estimation strategy to achieve better schedulability. Extensive simulation studies are carried out to investigate the effectiveness of this estimation strategy versus its cost.     

A deliberative scheduling technique for a real-time agent architecture

In this paper, we present a heuristic to schedule complex task models (tasks that use Artificial Intelligence methods). These tasks are used in a real-time agent architecture called ARTIS. This architecture has been designed to build intelligent agents that work in hard real-time environments. To do this, the architecture provides scheduling at two levels. The first level assures the fulfilment of the hard temporal requirements, and the second level obtains a result of higher quality. The new heuristic, Slack-Slide Scheduling (SSS), works at the second level. It manages two types of methods: progressive refinement methods and multiple methods. The Slack-Slide Scheduling also attempts to reuse previous results in order to make better use of the existing CPU time while the first-level scheduler fulfils the deadlines.     

Some algorithms for analysis and synthesis of real-time multiprocessor computing systems

The problem of preemptive scheduling in a real-time multiprocessor computing system with release time/deadline intervals is investigated. Approximate algorithms based on the generalization of a single-processor algorithm of relative priority are developed and compared to the exact maximum flow algorithm. An algorithm has been developed for the case where requests for the tasks occur periodically with given periods. An algorithm for determining the values of the processor performance for which there exists an admissible schedule for a given assembly of tasks with release time/deadline intervals has been developed.     

Real-time task scheduling with fuzzy uncertainty in processing times and deadlines

In real-time systems, scheduling algorithms play the vital role of devising a feasible schedule of the tasks. The scheduling algorithm designer faces uncertainty associated with the timing constrains of the real-time tasks. This paper considers fuzzy timing constraints by modeling the real-time tasks with fuzzy deadlines and fuzzy processing times with different membership functions. Comparative studies and some interesting findings based on simulation experiments are reported.     

I/O issues in a multimedia system

In future computer system design, I/O systems will have to support continuous media such as video and audio, whose system demands are different from those of data such as text. Multimedia computing requires us to focus on designing I/O systems that can handle real-time demands. Video- and audio-stream playback and teleconferencing are real-time applications with different I/O demands. We primarily consider playback applications which require guaranteed real-time I/O throughput. In a multimedia server, different service phases of a real-time request are disk, small computer systems interface (SCSI) bus, and processor scheduling. Additional service might be needed if the request must be satisfied across a local area network. We restrict ourselves to the support provided at the server, with special emphasis on two service phases: disk scheduling and SCSI bus contention. When requests have to be satisfied within deadlines, traditional real-time systems use scheduling algorithms such as earliest deadline first (EDF) and least slack time first. However, EDF makes the assumption that disks are preemptable, and the seek-time overheads of its strict real-time scheduling result in poor disk utilization. We can provide the constant data rate necessary for real-time requests in various ways that require trade-offs. We analyze how trade-offs that involve buffer space affect the performance of scheduling policies. We also show that deferred deadlines, which increase buffer requirements, improve system performance significantly     

Scheduling parallel Kalman filters with quantized deadlines

In this paper we explore the problem of scheduling parallel processes of Kalman filters to meet individual estimation error requirements. It is assumed that at each time-step measurements of only one process are received. We define real-time deadlines of transmissions and convert the problem into arranging sequence of tasks with corresponding deadlines. To reduce computations, cycles of transmissions are calculated and virtual processes are introduced into scheduling. A sliding window method is then designed to adjust the processes against real-time disturbances in applications. Compared with algorithms proposed in Lin and Wang (2013), the proposed algorithm is able to schedule a feasible sequence adaptively within a short scheduling window and requires little computation.     

Real-time service process admission control with schedule reorganization

This paper addresses the problem of resource reservation for applications using the real-time service-oriented architecture paradigm. Real-time services must be completed by their deadlines. They can be scheduled anywhere within an execution interval. Some services have a large execution interval which gives them more flexibility during admission control. However, the conventional approach for real-time process scheduling is to reserve a fixed schedule on the first come, first served basis and thus does not take advantage of this flexibility. In this paper, a reorganization algorithm is presented to relocate existing reservations in order to accommodate new requests that have less flexibility. For service process reservations, intermediate deadlines may also be adjusted to further increase the flexibility of service reservations. Simulation results show that reorganization can greatly enhance the acceptance ratio of real-time requests in most situations.     

实时异构系统的动态分批优化调度算法

提出了一种实时异构系统的动态分批优化调度算法,该算法采用的是在每次扩充当前局部调度时,按一定规则在待调度的任务集中选取一批任务,对该批任务中的每项任务在每个处理器上的运行综合各种因素构造目标函数,将问题转化为非平衡分配问题,一次性为这些任务都分配一个处理器或为每个处理器分配一项任务,使得这种分配具有最好的“合适性”,以增大未被调度任务的可行性.这种方法有效地提高了算法调度成功率.同时,为了评估该算法的性能,对其进行了大量的模拟,分析了一些任务参数的变化对算法调度成功率的影响,并与老算法的调度成功率进行了比较.模拟结果显示,新算法优于老算法.     

一种新颖的带模糊截止时限的磁盘调度算法

设计了一种新的基于截止时限的磁盘调度算法,该算法支持带多优先级的请求。对于某些实时要求,其截止时限是不确定的或者不精确的,该算法采用模糊集来描述这类不确定性,模糊截止时限的隶属度函数表示对请求完成时间的满意程度。调度的目的是最优的指定优先级,使得截止时限的满意程度最大化。根据请求截止时限的不同,把满意程度划分为若干连续的区间。在每个不同的区间内,每个请求都对应有修正的截止时限,把请求按照其修正的截止时限非减的顺序分配优先级,才能实现请求优先级的最优配置。仿真结果表明该算法能有效的分配请求的优先级,降低请求的丢失率,保证了更多的请求得到满足。     

Dynamic real-time scheduling strategies for interactive continuous media servers

In this paper, we propose and study a dynamic approach to schedule real-time requests in a video-on-demand (VOD) server. Providing quality of service in such servers requires uninterrupted and on-time retrieval of motion video data. VOD services and multimedia applications further require access to the storage devices to be shared among multiple concurrent streams. Most of the previous VOD scheduling approaches use limited run-time,0 information and thus cannot exploit the potential capacity of the system fully. Our approach improves throughput by making use of run-time information to relax admission control. It maintains excellent quality of service under varying playout rates by observing deadlines and by reallocating resources to guarantee continuous service. It also reduces start-up latency by beginning service as soon as it is detected that deadlines of all real-time requests will be met. We establish safe conditions for greedy admission, dynamic control of disk read sizes, fast initial service, and sporadic services. We conduct thorough simulations over a wide range of buffer capacities, load settings, and over varying playout rates to demonstrate the significant improvements in quality of service, throughput and start-up latency of our approach relative to a static approach.     

An optimal boundary fair scheduling algorithm for multiprocessor real-time systems

With the emergence of multicore processors, the research on multiprocessor real-time scheduling has caught more researchers’ attention recently. Although the topic has been studied for decades, it is still an evolving research field with many open problems. In this work, focusing on periodic real-time tasks with quantum-based computation requirements and implicit deadlines, we propose a novel optimal scheduling algorithm, namely boundary fair (Bfair), which can achieve full system utilization as the well-known Pfair scheduling algorithms. However, different from Pfair algorithms that make scheduling decisions and enforce proportional progress (i.e., fairness) for all tasks at each and every time unit, Bfair makes scheduling decisions and enforces fairness to tasks only at tasks’ period boundaries (i.e., deadlines of periodic tasks). The correctness of the Bfair algorithm to meet the deadlines of all tasks’ instances is formally proved and its performance is evaluated through extensive simulations. The results show that, compared to that of Pfair algorithms, Bfair can significantly reduce the number of scheduling points (by up to 94%) and the overhead of Bfair at each scheduling point is comparable to that of the most efficient Pfair algorithm (i.e., PD²). Moreover, by aggregating the time allocation of tasks for the time interval between consecutive period boundaries, the resulting Bfair schedule can dramatically reduce the number of required context switches and task migrations (as much as 82% and 85%, respectively) when compared to those of Pfair schedules, which in turn reduces the run-time overhead of the system.     

To Schedule or to Execute: Decision Support and Performance Implications

This paper addresses a fundamental trade-off in dynamic scheduling between the cost of scheduling and the quality of the resulting schedules. The time allocated to scheduling must be controlled explicitly, in order to obtain good-quality schedules in reasonable times. As task constraints are relaxed, the algorithms proposed in this paper increase scheduling complexity to optimize longer and obtain high-quality schedules. When task constraints are tightened, the algorithms adjust scheduling complexity to reduce the adverse effect of long scheduling times on the schedule quality. We show that taking into account the scheduling time is crucial for honoring the deadlines of scheduled tasks. We investigate the performance of our algorithms in two scheduling models: one that allows idle-time intervals to exist in the schedule and another that does not. The model with idle-time intervals has important implications for dynamic scheduling which are discussed in the paper. Experimental evaluation of the proposed algorithms shows that our algorithms outperform other candidate algorithms in several parameter configurations.