Fault-tolerant Scheduling Research Articles

Dynamic fault tolerant scheduling policy for workflows in Grid computing

Dynamic fault tolerant scheduling policy for workflows in Grid computing

Redundant and fault-tolerant algorithms for real-time measurement and control systems for weapon equipment

Because of the high availability requirements from weapon equipment, an in-depth study has been conducted on the real-time fault-tolerance of the widely applied Compact PCI (CPCI) bus measurement and control system. A redundancy design method that uses heartbeat detection to connect the primary and alternate devices has been developed. To address the low successful execution rate and relatively large waste of time slices in the primary version of the task software, an improved algorithm for real-time fault-tolerant scheduling is proposed based on the Basic Checking available time Elimination idle time (BCE) algorithm, applying a single-neuron self-adaptive proportion sum differential (PSD) controller. The experimental validation results indicate that this system has excellent redundancy and fault-tolerance, and the newly developed method can effectively improve the system availability.

Dynamic and Adaptive Fault Tolerant Scheduling With QoS Consideration in Computational Grid

Provisioning fault-tolerant scheduling in computational grid is a challenging task. Most of the existing fault tolerant scheduling schemes are either geared toward proactive or reactive. Proactive schemes emphasize on the reasons responsible for generating faults, whereas reactive mechanisms come into effect after failure detection. Unlike most existing mechanisms, we present a novel, dynamic, adaptive, and hybrid fault-tolerant scheduling scheme based on proactive and reactive approaches. In the proactive approach, the resource filtration algorithm picks resources based on resource location, availability, and reliability. Unlike most existing schemes, which rely on remotely connected resources, the proposed algorithm prefers to employ locally available resources as they might have less failure tendency. To cope with the frequent turnover problem, the proposed scheme calculates resource availability time based on various newly identified parameters (e.g., mean time between availability) and picks highly available nodes for task execution. Resource reliability is an indispensable consideration in the proposed scheme and is calculated based on parameters such as jobs success or failure ratio and the types of failures encountered. We employ an optimal resource identification algorithm to determine and select optimal resources for job execution. The performance of the proposed scheme is validated through the GridSim toolkit. Compared with contemporary approaches, experimental results demonstrate the effectiveness and efficiency of the proposed scheme in terms of various performance metrics, such as wall clock time, throughput, waiting and turnaround time, number of checkpoints, and energy consumption.

Fault-Tolerant Scheduling for Real-Time Scientific Workflows with Elastic Resource Provisioning in Virtualized Clouds

Clouds are becoming an important platform for scientific workflow applications. However, with many nodes being deployed in clouds, managing reliability of resources becomes a critical issue, especially for the real-time scientific workflow execution where deadlines should be satisfied. Therefore, fault tolerance in clouds is extremely essential. The PB (primary backup) based scheduling is a popular technique for fault tolerance and has effectively been used in the cluster and grid computing. However, applying this technique for real-time workflows in a virtualized cloud is much more complicated and has rarely been studied. In this paper, we address this problem. We first establish a real-time workflow fault-tolerant model that extends the traditional PB model by incorporating the cloud characteristics. Based on this model, we develop approaches for task allocation and message transmission to ensure faults can be tolerated during the workflow execution. Finally, we propose a dynamic fault-tolerant scheduling algorithm, FASTER, for realtime workflows in the virtualized cloud. FASTER has three key features: 1) it employs a backward shifting method to make full use of the idle resources and incorporates task overlapping and VM migration for high resource utilization, 2) it applies the vertical/horizontal scaling-up technique to quickly provision resources for a burst of workflows, and 3) it uses the vertical scaling-down scheme to avoid unnecessary and ineffective resource changes due to fluctuated workflow requests. We evaluate our FASTER algorithm with synthetic workflows and workflows collected from the real scientific and business applications and compare it with six baseline algorithms. The experimental results demonstrate that FASTER can effectively improve the resource utilization and schedulability even in the presence of node failures in virtualized clouds.

Hybrid Software Redundancy Approach for Building Reliable Communication in Multi-BUS Heterogeneous Systems

The paper proposes a new reliable fault-tolerant scheduling algorithm for real-time embedded systems. The proposed algorithm is based on static scheduling that allows to include the dependencies and the execution cost of tasks and data dependencies in its scheduling decisions. Our scheduling algorithm is dedicated to multi-bus heterogeneous architectures with multiple processors linked by several shared buses. This scheduling algorithm is considering only one bus fault caused by hardware faults and compensated by software redundancy solutions. The proposed algorithm is based on both active and passive backup copies to minimize the scheduling length of data on buses. In the experiments, the proposed methods are evaluated in terms of data scheduling length for a set of DSP benchmarks. The experimental results show the effectiveness of our technique.

An Efficient Fault-Tolerant Multi-Bus Data Scheduling Algorithm Based on Replication and Deallocation

Abstract The paper proposes a new reliable fault-tolerant scheduling algorithm for real-time embedded systems. The proposed scheduling algorithm takes into consideration only one bus fault in multi-bus heterogeneous architectures, caused by hardware faults and compensated by software redundancy solutions. The proposed algorithm is based on both active and passive backup copies, to minimize the scheduling length of data on buses. In the experiments, this paper evaluates the proposed methods in terms of data scheduling length for a set of DAG benchmarks. The experimental results show the effectiveness of our technique.

Worst-Case Finish Time Analysis for DAG-Based Applications in the Presence of Transient Faults

Tasks in hard real-time systems are required to meet preset deadlines, even in the presence of transient faults, and hence the analysis of worst-case finish time (WCFT) must consider the extra time incurred by re-executing tasks that were faulty. Existing solutions can only estimate WCFT and usually result in significant under- or over-estimation. In this work, we conclude that a sufficient and necessary condition of a task set experiencing its WCFT is that its critical task incurs all expected transient faults. A method is presented to identify the critical task and WCFT in O(|V | + |E|) where |V | and |E| are the number of tasks and dependencies between tasks, respectively. This method finds its application in testing the feasibility of directed acyclic graph (DAG) based task sets scheduled in a wide variety of fault-prone multi-processor systems, where the processors could be either homogeneous or heterogeneous, DVS-capable or DVS-incapable, etc. The common practices, which require the same time complexity as the proposed critical-task method, could either underestimate the worst case by up to 25%, or overestimate by 13%. Based on the proposed critical-task method, a simulated-annealing scheduling algorithm is developed to find the energy efficient fault-tolerant schedule for a given DAG task set. Experimental results show that the proposed critical-task method wins over a common practice by up to 40% in terms of energy saving.

Fault Tolerant Global Scheduling with Backup Priority Promotion

Fault Tolerant Global Scheduling with Backup Priority Promotion

Design of a Fault Tolerant Load Balancing Scheduler for Computational

Grid is a collection of heterogeneous resources from a decentralized management. These resources are from large number of organizations and each resource with a local administration and scheduling policy are connected by wide area network. Due to these factors, strong variations prevail in the availability of grid resources and lead to increase in the probability of failures than in traditional parallel and distributed systems. An efficient fault tolerant scheduling approach is needed to schedule the jobs to the appropriate resources which can handle the failure nature of grid resources. Load balancing is required to improve the utilization of the resources and throughput. In this paper, a new scheduling approach is proposed that schedules the grid tasks by considering the failure rate of the resources in order to handle task failures. The proposed Fault tolerant Load Balancing (FTLB) algorithm increases the execution success rate and improves makespan. This algorithm also considers load of each resource while scheduling the jobs to increase resource utilization and throughput of the system. By considering user demand such as deadline for job completion, it improves user satisfaction. The analysis of the experimental results proves that the proposed FTLB algorithm has improved makespan, hit rate and average resource utilization than the existing algorithms.

Low power fault tolerance scheduling scheme in DVS-enabled real-time systems

This paper investigates the power management and fault tolerance in DVS-enabled real-time systems based on the EDF scheme. The power management is achieved via dynamic voltage scaling DVS and fault tolerance is achieved via checkpoint scheme. We estimate a critical speed which effectively decreases the energy consumption by the associated frequency dependent and independent devices. The proposed low power fault tolerance scheduling scheme includes two parts: 1 an offline solution to compute the optimal number of checkpoints and the running speed; 2 an online speed reduction mechanism based on the actual workload by using the slack time. The experimental results show that the proposed approach which is compared to the previous method Melhem et al., 2004 significantly reduces the energy consumption.

A Real-Time Task Availability Improving Fault-Tolerant Scheduling Algorithm on Heterogeneous Platform

A Real-Time Task Availability Improving Fault-Tolerant Scheduling Algorithm on Heterogeneous Platform

Improving Fault-Tolerant Load Balancing Algorithms in Computational Grids

Fault tolerant scheduling of many jobs in an environment with millions of unpredictable nodes is not an easy issue. To the best of our knowledge, no work in the literature has proposed a solution that combines the merits of active and passive replication schemes of fault tolerance with the advantages of performance-driven load balancing so as to make the most of the strong points of each. While extensive fault tolerant scheduling and load balancing methods have been presented for the sequential jobs, none have taken into account fault-tolerant load balancing that minimizes the job make-span, provides efficient network and node utilization, achieves a Ill-balanced load and high system flexibility even during the resource failures. Hence, in this article, I present an Adaptive Scheduling Algorithm namely ASA that overcomes these problems. With thorough simulations, I conclude that ASA allocates any number of jobs to a million nodes with relatively low overhead and high flexibility. Experimental results show that the performance of ASA is better than those of its counterparts.

Fault-Tolerant Scheduling for Real-Time Tasks on Multiple Earth-Observation Satellites

Fault-tolerance plays an important role in improving the reliability of multiple earth-observing satellites, especially in emergent scenarios such as obtaining photographs on battlefields or earthquake areas. Fault tolerance can be implemented through scheduling approaches. Unfortunately, little attention has been paid to fault-tolerant scheduling on satellites. To address this issue, we propose a novel dynamic fault-tolerant scheduling model for real-time tasks running on multiple observation satellites. In this model, the primary-backup policy is employed to tolerate one satellite’s permanent failure at one time instant. In the light of the fault-tolerant model, we develop a novel f ault- t olerant s atellite s cheduling algorithm named FTSS. To improve the resource utilization, we apply the overlapping technology that includes primary-backup copy overlapping (i.e., PB overlapping) and backup-backup copy overlapping (i.e., BB overlapping). According to the satellites characterized with time windows for observations, we extensively analyze the overlapping mechanism on satellites. We integrate the overlapping mechanism with FTSS, which employs the task merging strategies including primary-backup copy merging (i.e., PB merging), backup-backup copy merging (i.e., BB merging) and primary-primary copy merging (i.e., PP merging). These merging strategies are used to decrease the number of tasks required to be executed, thereby enhancing system schedulability. To demonstrate the superiority of our FTSS, we conduct extensive experiments using the real-world satellite parameters supplied from the satellite tool kit or STK; we compare FTSS with the three baseline algorithms, namely, NMFTSS, NOFTSS, and NMNOFTSS. The experimental results indicate that FTSS efficiently improves the scheduling quality of others and is suitable for fault-tolerant satellite scheduling.

Fault Tolerant Scheduling for Parallel Loops on Shared Memory Systems

While multicore/multiprocessor systems achieve significant speedup for many applications by exploiting loop level parallelism, they also suffer from increased reliability problems as a result of ever scaling device size. This paper addresses the reliability of loop dominated applications, aiming to execute parallel loops efficiently in the presence of various types of hardware faults. In this paper, we present a fault tolerant work-stealing scheme which makes parallel loop execution resilient to hardware faults. A lightweight buffer-commit mechanism is applied in the proposed scheme to ensure the correctness of the re-execution of loop iterations. In addition, we split large failing chunks of loop iterations at runtime to improve load balancing, and a worker thread is discarded when faults occur frequently on it. We evaluated our techniques on a multi-socket multicore system, using a set of loop dominated benchmarks. The proposed scheme achieves the minimum overhead of supporting fault tolerance and optimal load balancing.

Dynamic Replication of Fault-Tolerant Scheduling Algorithm

In order to reduce the impact on the grid scheduling caused by the resource error, for complex dependent tasks, designed a dynamic replication of fault-tolerant scheduling algorithm (DRFT). This algorithm build task model by applying hypergraph theory, using primary-backup task as backup mode, take the active execution mode combined with the passive execution mode to perform the backup task, set up dynamic backup level according to the level of importance and resources security condition of dependent task, pursuit time of the task execution is minimized, the simulation result shows that the algorithm can still be accomplished scheduling quickly in case of error caused by the resource, to make up the shortage of common algorithms in terms of fault-tolerant.

FESTAL: Fault-Tolerant Elastic Scheduling Algorithm for Real-Time Tasks in Virtualized Clouds

As clouds have been deployed widely in various fields, the reliability and availability of clouds become the major concern of cloud service providers and users. Thereby, fault tolerance in clouds receives a great deal of attention in both industry and academia, especially for real-time applications due to their safety critical nature. Large amounts of researches have been conducted to realize fault tolerance in distributed systems, among which fault-tolerant scheduling plays a significant role. However, few researches on the fault-tolerant scheduling study the virtualization and the elasticity, two key features of clouds, sufficiently. To address this issue, this paper presents a fault-tolerant mechanism which extends the primary-backup model to incorporate the features of clouds. Meanwhile, for the first time, we propose an elastic resource provisioning mechanism in the fault-tolerant context to improve the resource utilization. On the basis of the fault-tolerant mechanism and the elastic resource provisioning mechanism, we design novel fault-tolerant elastic scheduling algorithms for real-time tasks in clouds named FESTAL, aiming at achieving both fault tolerance and high resource utilization in clouds. Extensive experiments injecting with random synthetic workloads as well as the workload from the latest version of the Google cloud tracelogs are conducted by CloudSim to compare FESTAL with three baseline algorithms, i.e., Non-M igration-FESTAL (NMFESTAL), Non-Overlapping-FESTAL (NOFESTAL), and Elastic First Fit (EFF). The experimental results demonstrate that FESTAL is able to effectively enhance the performance of virtualized clouds.

Optimal Checkpoint Selection with Dual-Modular Redundancy Hardening

With the continuous scaling of semiconductor technology, failure rate is increasing significantly so that reliability becomes an important issue in multiprocessor system-on-chip (MPSoC) design. We propose an optimal checkpoint selection with task duplication hardening to tolerate transient faults. A target application is specified in a task graph, and the schedule/checkpoint placements are determined at design time. The proposed optimal algorithm minimizes the checkpoint overhead with a latency constraint. Experimental results show that the proposed algorithm effectively reduces the minimum end-to-end latency to perform a fault-tolerant schedule. In addition, the proposed algorithm dramatically decreases the checkpointing overhead on uniprocessor and multiprocessor systems compared with a greedy approach and an equidistant algorithm.

Supporting fault-tolerance in a compositional real-time scheduling framework

Component-based analysis allows a robust time and space decomposition of a complex real-time system into components, which are then recomposed and hierarchically scheduled under potentially different scheduling policies. This mechanism is of great benefit to many critical systems as it enables fault isolation. To provide fault-tolerant scheduling in a compositional real-time scheduling framework, a few works have recently emerged, but remain inefficient in providing fault isolation or in terms of resource utilization. In this paper, we introduced a new interface model that takes into account the fault requirements of a component, and a fault-tolerant resource model that helps the component to effectively respond to each of its child components in presence of a fault. Finally, we analyzed the schedulability of the framework considering the Rate Monotonic scheduling algorithm.

A design fix to supervisory control for fault-tolerant scheduling of real-time multiprocessor systems with aperiodic tasks

In the article ‘Supervisory control for fault-tolerant scheduling of real-time multiprocessor systems with aperiodic tasks’, Park and Cho presented a systematic way of computing a largest fault-tolerant and schedulable language that provides information on whether the scheduler (i.e., supervisor) should accept or reject a newly arrived aperiodic task. The computation of such a language is mainly dependent on the task execution model presented in their paper. However, the task execution model is unable to capture the situation when the fault of a processor occurs even before the task has arrived. Consequently, a task execution model that does not capture this fact may possibly be assigned for execution on a faulty processor. This problem has been illustrated with an appropriate example. Then, the task execution model of Park and Cho has been modified to strengthen the requirement that none of the tasks are assigned for execution on a faulty processor.

Fault-Tolerant Dynamic Rescheduling for Heterogeneous Computing Systems

As the scale and complexity of heterogeneous computing systems grow, failures occur frequently and have an adverse effect on solving large-scale applications. Hence, fault-tolerant scheduling is an imperative step for large-scale computing systems. The existing fault-tolerant scheduling algorithms belong to static scheduling, and they allocate multiple copies of each task to several processors no matter whether processor failures affect the execution of tasks. Such active replication strategies not only waste resource but also sacrifice the makespan. What is more, they cannot guarantee the successful execution of applications. In this paper, we propose a fault-tolerant dynamic rescheduling algorithm named FTDR, which can overcome above drawbacks. FTDR keeps listening to the processor failure, and reschedules the suspended tasks once failures occur. Because FTDR reschedules the tasks that are suspended because of failures, it can tolerate an arbitrary number of failures. Randomly generated DAGs are tested in our experiments. Experimental results show that the proposed algorithm achieves good performance in terms of makespan and resource consumption compared with its direct competitors.