一种高效的合作实时事务并行检验点算法

许多数据和活动上都有很强时间性的应用在地理上同时具有分布性,这种应用需求使得分布式实时数据库的研完成为数据库研究领域的热点。在实时事务执行时,事务故障或数据竞争会导致事务重启,为了减少因重启而损失的工作量,可以采用检验点技术以利于事务时间正确性的满足。在一些分布式实时数据库应用中,不同结点的事务通过消息交换形成合作关系,当某一事务记检验点时,为保证合作事务间的全局一致性,相关事务也要相应地记检验点。传统的协同检验点方法没有考虑应用的定时约束,不能很好地支持分布式实时事务处理。本文提出了一种高效的并行协同检验点方法,该算法既具有最小协同检验点特性又使全局检验点过程延时最小。实验表明该算法减少了全局检验点阻塞时间,有利于分布式实时事务截止期的满足。     

Probabilistic optimisation of checkpoint intervals for real-time multi-tasks

This article considers the checkpoint placement problem for real-time systems. In our environment, multiple real-time tasks with arbitrary periods are scheduled in the system by the rate monotonic algorithm, and checkpoints are inserted at a constant interval in each task while the width of the interval is different with respect to the task. We derive an explicit formula of the probability that all the tasks are successfully completed with a given set of checkpoint intervals. Then we determine the optimal checkpoint intervals that maximise the probability of task completion. The probability computation includes the schedulability analysis with respect to the numbers of re-executed checkpoint intervals. Our method does not necessitate any algebraic condition on the periods of the scheduled tasks.     

Checkpoint Management with Double Modular Redundancy Based on the Probability of Task Completion

This paper proposes a checkpoint rollback strategy for real-time systems with double modular redundancy.Without built-in fault-detection and spare processors,our scheme is able to recover from both transient and permanent faults.Two comparisons are conducted at each checkpoint.First,the states stored in two consecutive checkpoints of one processor are compared for checking integrity of the processor.The states of two processors are also compared for detecting faults and the system rolls back to the previous checkpoint whenever required by logic of the proposed scheme.A Markov model is induced by the fault recovery scheme and analyzed to provide the probability of task completion within its deadline.The optimal number of checkpoints is selected so as to maximize the probability of task completion.     

A fully informed model-based checkpointing protocol for preventing useless checkpoints

Checkpointing and rollback recovery are widely used techniques for handling failures in distributed systems. When processes involved in a distributed computation are allowed to take checkpoints independently without any coordination with each other, some or all of the checkpoints taken may not be part of any consistent global checkpoint, and hence, are useless for recovery. Communication-induced checkpointing algorithms allow processes to take checkpoints independently and also ensure that each checkpoint taken is part of a consistent global checkpoint by forcing processes to take some additional checkpoints. It is well known that it is impossible to design an optimal communication-induced checkpointing algorithm (i.e. a checkpointing algorithm that takes minimum number of forced checkpoints). So, researchers have designed communication-induced checkpointing algorithms that reduce forced checkpoints using different heuristics. In this paper, we present a communication-induced checkpointing algorithm which takes less number of forced checkpoints when compared to some of the existing checkpointing algorithms in its class.     

A Feasibility Decision Algorithm for Rate Monotonic and Deadline Monotonic Scheduling

Rate monotonic and deadline monotonic scheduling are commonly used for periodic real-time task systems. This paper discusses a feasibility decision for a given real-time task system when the system is scheduled by rate monotonic and deadline monotonic scheduling. The time complexity of existing feasibility decision algorithms depends on both the number of tasks and maximum periods or deadlines when the periods and deadlines are integers. This paper presents a new necessary and sufficient condition for a given task system to be feasible and proposes a new feasibility decision algorithm based on that condition. The time complexity of this algorithm depends solely on the number of tasks. This condition can also be applied as a sufficient condition for a task system using priority inheritance protocols to be feasible with rate monotonic and deadline monotonic scheduling.     

Real-time task scheduling by multiobjective genetic algorithm

Real-time tasks are characterized by computational activities with timing constraints and classified into two categories: a hard real-time task and a soft real-time task. In hard real-time tasks, tardiness can be catastrophic. The goal of hard real-time tasks scheduling algorithms is to meet all tasks’ deadlines, in other words, to keep the feasibility of scheduling through admission control. However, in the case of soft real-time tasks, slight violation of deadlines is not so critical.In this paper, we propose a new scheduling algorithm for soft real-time tasks using multiobjective genetic algorithm (moGA) on multiprocessors system. It is assumed that tasks have precedence relations among them and are executed on homogeneous multiprocessor environment.The objective of the proposed scheduling algorithm is to minimize the total tardiness and total number of processors used. For these objectives, this paper combines adaptive weight approach (AWA) that utilizes some useful information from the current population to readjust weights for obtaining a search pressure toward a positive ideal point. The effectiveness of the proposed algorithm is shown through simulation studies.     

Optimal Control of Multi-Stage Discrete Event Systems With Real-Time Constraints

We consider discrete event systems involving tasks with real-time constraints and seek to control processing times so as to minimize a cost function subject to each task meeting its own constraint. When tasks are processed over a single stage, it has been shown that there are structural properties of the optimal state trajectory that lead to very efficient solutions of such problems. When tasks are processed over multiple stages and are subject to end-to-end real-time constraints, these properties no longer hold and no obvious extensions are known. We consider such a multi-stage problem with not only stage-dependent but also task-dependent cost functions over all tasks at each stage and derive several new optimality properties. These properties lead to the idea of introducing ldquovirtualrdquo deadlines at each stage except the last one, thus partially decoupling the stages so that the known efficient solutions for single-stage problems can be used. We prove that a sequence of solutions to single-stage problems with virtual deadlines updated at each step converges to the global optimal solution of the multi-stage problem. This leads to a virtual deadline algorithm (VDA) which is scalable in the number of processed tasks. We illustrate the scalability and efficiency of the VDA through numerical examples.     

Fault-Tolerant Scheduling for Real-Time Embedded Control Systems

With the increasing complexity of industrial application, an embedded control system (ECS) requires processing a number of hard real-time tasks and needs fault-tolerance to assure high reliability. Considering the characteristics of real-time tasks in ECS, an integrated algorithm is proposed to schedule real-time tasks and to guarantee that all real-time tasks are completed before their deadlines even in the presence of faults. Based on the nonpreemptive critical-section protocol (NCSP), this paper analyzes the blocking time introduced by resource conflicts of relevancy tasks in fault-tolerant multiprocessor systems. An extended schedulability condition is presented to check the assignment feasibility of a given task to a processor. A primary/backup approach and on-line replacement of failed processors are used to tolerate processor failures. The analysis reveals that the integrated algorithm bounds the blocking time, requires limited overhead on the number of processors, and still assures good processor utilization. This is also demonstrated by simulation results. Both analysis and simulation show the effectiveness of the proposed algorithm in ECS.     

Checkpoint space reclamation for uncoordinated checkpointing inmessage-passing systems

Uncoordinated checkpointing allows process autonomy and general nondeterministic execution, but suffers from potential domino effects and the associated space overhead. Previous to this research, checkpoint space reclamation had been based on the notion of obsolete checkpoints; as a result, a potentially unbounded number of nonobsolete checkpoints may have to be retained on stable storage. In this paper, we derive a necessary and sufficient condition for identifying all garbage checkpoints. By using the approach of recovery line transformation and decomposition, we develop an optimal checkpoint space reclamation algorithm and show that the space overhead for uncoordinated checkpointing is in fact bounded by N(N+1)/2 checkpoints where N is the number of processes     

分布式共享主存结构动态检查点技术的应用研究

介绍在传统检查点技术的基础上提出一种面向分布式共享主存结构计算机节点瞬时故障的动态检查点技术。通过对节点及其运行进程的实时监控数据的分析，给出检查点的引入、保存、恢复和取消的容错技术策略。同时分析该技术在一定的故障模型下，对不同应用程序的有效程度及其应用开销。目的是希望使检查点序列在覆盖故障点的同时，尽可能降低保存检查点的次数，提高系统运行效率。     

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.     

Enhancing the Schedulability of Real-Time Heterogeneous Networks of Workstations (NOWs)

This paper proposes a realtime duplication based algorithm (RT-DBA) for scheduling precedence-related periodic tasks with hard deadlines on networks of workstations (NOWs). We have utilized selective subtask duplication that enables some tasks to have earlier start times, which enables additional tasks (and, hence, task sets) to finish before their deadlines, thereby increasing the schedulability of a real-time application. We strongly believe that duplication can be used as a tool for obtaining a better quality of service (QoS) from the real-time heterogeneous system, and this is our major contribution. We have taken both the computation and the communication heterogeneities into account while modeling such a system. Both data and control dependencies between the tasks have also been considered. Our algorithm exhibits scalability, fully exploits the underlying parallelism, and is capable of scheduling an application, even if the available number of processors is less than the required number of processors. Based on extensive simulation studies, we observe that RT-DBA offers an enhanced success ratio as compared to other scheduling schemes when communication is a dominant factor.     

Period sensitivity analysis and D-P domain feasibility region in dynamic priority systems

In the design of a real-time application it is fundamental to know how a change in the task parameters would affect the feasibility of the system. Relaxing the classical assumptions on static task sets with fixed periods and deadlines can give higher resource utilisation and better performance. But the changes on task parameters have to be done always maintaining feasibility. In practice, period and deadline modifications are only necessary on single tasks. Our work focuses on finding the feasibility region of deadlines and periods (called D-P feasibility region) for a single task in the context of dynamic, uniprocessor scheduling of hard real-time systems. This way, designers can choose the optimal deadline and period pairs that best fit application requirements. We provide an exact and an approximated algorithm to calculate this region. We will show that the approximated solution is very close to the exact one and it takes considerably less time.     

支持移动合作实时事务的一种新的协同检验点算法

现有的协同检验点方法在移动环境中会带来较大的检验点过程延时 ,不能很好地支持实时事务处理 .提出了一种新的协同并行检验点方法 ,在正常的消息传输过程中 ,通过一点额外的带宽传送事务间检验点依赖关系 ;在某一事务记检验点时 ,尽可能地同时通知相关的事务记检验点 .实验表明 ,该算法对网络带宽没有明显的增加 ,而能大大降低事务记检验点的延时 ,使系统中超截止期的事务比例大大降低     

Real-Time Performance of Sorting Algorithms

In hard real-time systems tasks must meet their deadlines under guarantee. Soft real-time tasks may miss deadlines occasionally, as long as the entire system can provide the specified quality of service.In this paper we investigate the hard and soft real-time performance of sorting algorithms and compare it to their average performance. We show in which way the adequacy of an algorithm depends on the demanded performance criterium (hard, soft, or non real-time). The results provide a guideline to select the right sorting algorithm for a given application.     

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.     

支持分布式合作实时事务处理的协同检验点方法

在实时事务执行时，事务故障或数据竞争会导致事务重启，为减少事务重启损失的工作量，可以采用检验点技术保证事务的时间正确性．在一类分布式实时数据库应用中，不同结点的事务通过消息交换形成合作关系，为保证合作事务间的全局一致性，当某一事务记检验点时，相关事务也要记检验点．传统协同检验点方法没有考虑应用的定时约束，不能很好地支持分布式合作实时事务处理．该文提出了一种基于图论的协同检验点方法，利用在每个计算结点上为每个合作事务集维护的局部有向图，使用一个基于图论的计算过程标识出应记检验点的事务，该方法既具有最小协同检验点特性，又使全局检验点的时延最小．实验表明该算法减少了全局检验点时延，有利于实时事务截止期的满足．     

Aperiodic task scheduling for Hard-Real-Time systems

A real-time system consists of both aperiodic and periodic tasks. Periodic tasks have regular arrival times and hard deadlines. Aperiodic tasks have irregular arrival times and either soft or hard deadlines. In this article, we present a new algorithm, the Sporadic Server algorithm, which greatly improves response times for soft deadline aperiodic tasks and can guarantee hard deadlines for both periodic and aperiodic tasks. The operation of the Sporadic Server algorithm, its performance, and schedulability analysis are discussed and compared with previously published aperiodic service algorithms.     

Scheduling Tasks with Resource Requirements in Hard Real-Time Systems

This paper describes a heuristic approach for solving the problem of dynamically scheduling tasks in a real-time system where tasks have deadlines and general resource requirements. The crux of our approach lies in the heuristic function used to select the task to be scheduled next. The heuristic function is composed of three weighted factors. These factors explicitly consider information about real-time constraints of tasks and their utilization of resources. Simulation studies show that the weights for the various factors in the heuristic function have to be fine-tuned in order to obtain a degree of success in the range of 75-88 percent of that obtained via exhaustive search. However, modifying the approach to use limited backtracking improves the degree of success substantially to as high as 99.5 percent. This improvement is observed even when the initial set of weights are not tailored for a particular set of tasks. Simulation studies also show that in most cases the schedule determined by the heuristic algorithm is optimal or close to optimal.     

Aperiodic servers in a deadline scheduling environment

A real-time system may have tasks with soft deadlines, as well as hard deadlines. While earliest-deadline-first scheduling is effective for hard-deadline tasks, applying it to soft-deadline tasks may waste schedulable processor capacity or sacrifice average response time. Better average response time may be obtained, while still guaranteeing hard deadlines, with an aperiodic server. Three scheduling algorithms for aperiodic servers are described, and schedulability tests are derived for them. A simulation provides performance data for these three algorithms on random aperiodic tasks. The performances of the deadline aperiodic servers are compared with those of several alternatives, including background service, a deadline polling server, and rate-monotonic servers, and with estimates based on the M/M/1 queueing model. This adds to the evidence in support of deadline scheduling,versus fixed priority scheduling.