Checkpoint Placement Research Articles

Fault tolerance based load balancing approach for web resources

ABSTRACTGrid computing is a prominent tool for assembling and incorporating groups of heterogeneous resources scattered around the world, connected through a network. Since load balancing is a challenging issue in a distributed environment, Grid computing provides an architecture, which is well suited, low-cost, and consistent. For task execution on suitable resources, grid computing provides efficient load balancing and fault tolerance approaches. But, due to the dynamic nature of grid resources, sometimes tasks can’t be completed within given constraints (deadline, cost). To solve these issues, this paper proposes a fault tolerance–based load balancing approach by considering the dynamic nature of resources. First, significant contributions in the field of load balancing are analyzed based on several parameters. Second, a fault tolerance dynamic load balancing model is proposed for task execution based on resource load and fault index value. For fault tolerance, checkpoints are set at various determined intervals to resume tasks at the next possible instance that avoids unnecessary placement of checkpoints. Third, the proposed model is validated and provides improved performance in terms of response time, makespan, and throughput. The model provides up to 12% and 9% performance improvement depending on method of measurement in comparison to other state-of-the-art methods.

Optimum checkpoints for programs with loops

Checkpoints are widely used to improve the performance of computer systems and programs in the presence of failures, and they significantly reduce the overall cost of running a program, if the program or the underlying system, are subject to failures. Thus application level checkpointing has been proposed for programs which may execute on platforms which are prone to failures, and also to reduce the execution time of programs which are prone to internal failures. This paper develops a mathematical model to estimate the average execution time of a program in the presence of failures, without and with application level checkpointing, and we use it to predict the optimum interval number of instructions which should be executed between the placement of successive checkpoints. The case of programs with loops and nested loops is also discussed. The results are illustrated with several numerical examples.

Reliability Hardening Mechanisms in Cyber-Physical Digital-Microfluidic Biochips

In the area of biomedical engineering, digital-microfluidic biochips (DMFBs) have received considerable attention because of their capability of providing an efficient and reliable platform for conducting point-of-care clinical diagnostics. System reliability, in turn, mandates error-recoverability while implementing biochemical assays on-chip for medical applications. Unfortunately, the technology of DMFBs is not yet fully equipped to handle error-recovery from various microfluidic operations involving droplet motion and reaction. Recently, a number of cyber-physical systems have been proposed to provide real-time checking and error-recovery in assays based on the feedback received from a few on-chip checkpoints. However, to synthesize robust feedback systems for different types of DMFBs, certain practical issues need to be considered such as co-optimization of checkpoint placement, error-recoverability, and layout of droplet-routing pathways. For application-specific DMFBs, we propose here an algorithm that minimizes the number of checkpoints and determines their locations to cover every path in a given droplet-routing solution. Next, for general-purpose DMFBs, where the checkpoints are pre-deployed in specific locations, we present a checkpoint-aware routing algorithm such that every droplet-routing path passes through at least one checkpoint to enable error-recovery and to ensure physical routability of all droplets. Furthermore, we also propose strategies for executing the algorithms in reliable mode to enhance error-recoverability. The proposed methods thus provide reliability-hardening mechanisms for a wide class of cyber-physical DMFBs.

Optimizing checkpoint data placement with guaranteed burst buffer endurance in large-scale hierarchical storage systems

Non-volatile devices, such as SSDs, will be an integral part of the deepening storage hierarchy on large-scale HPC systems. These devices can be on the compute nodes as part of a distributed burst buffer service or they can be external. Wherever they are located in the hierarchy, one critical design issue is the SSD endurance under the write-heavy workloads, such as the checkpoint I/O for scientific applications. For these environments, it is widely assumed that checkpoint operations can occur once every 60 min and for each checkpoint step as much as half of the system memory can be written out. Unfortunately, for large-scale HPC applications, the burst buffer SSDs can be worn out much more quickly given the extensive amount of data written at every checkpoint step. One possible solution is to control the amount of data written by reducing the checkpoint frequency. However, a direct effect caused by reduced checkpoint frequency is the increased vulnerability window of system failures and therefore potentially wasted computation time, especially for large-scale compute jobs.In this paper, we propose a new checkpoint placement optimization model which collaboratively utilizes both the burst buffer and the parallel file system to store the checkpoints, with design goals of maximizing computation efficiency while guaranteeing the SSD endurance requirements. Moreover, we present an adaptive algorithm which can dynamically adjust the checkpoint placement based on the system’s dynamic runtime characteristics and continuously optimize the burst buffer utilization. The evaluation results show that by using our adaptive checkpoint placement algorithm we can guarantee the burst buffer endurance with at most 5% performance degradation per application and less than 3% for the entire system.

분산 고장 탐지 방식을 이용한 실시간 태스크에서의 최적 체크포인터 구간 선정

체크포인터를 삽입한 실시간 시스템에서는 고장이 발생하면 고장 직전의 체크포인터로 회귀하여 태스크를 재실행함으로써 과도 고장을 효과적으로 극복할 수 있다. 이번 논문에서는 체크포인터에서 실행되는 데이터 저장과 고장 탐지 과정을 분리한 새로운 체크포인터 방식을 제안한다. 하나의 체크포인터 구간 내에 여러 개의 고장 탐지 과정을 추가하면 고장 발생에서 탐지까지의 지연 시간을 줄일 수 있다. 본 논문에서는 태스크가 데드라인 이내에서 성공적으로 수행될 확률을 최대화하는 고장 탐지 과정의 삽입 방법을 제안한다. 고장 탐지 과정이 분리된 체크포인터 방식을 마코프 체인으로 모델링하고 실시간 태스크의 성공적 수행 확률을 계산하는 모의실험을 수행하여 최적의 해를 구하는 과정을 제시한다. Checkpoint placement is an effective fault tolerance technique against transient faults in which the task is re-executed from the latest checkpoint when a fault is detected. In this paper, we propose a new checkpoint placement strategy separating data saving and fault detection processes that are performed together in conventional checkpoints. Several fault detection processes are performed in one checkpoint interval in order to decrease the latency between the occurrence and detection of faults. We address the placement method of fault detection processes to maximize the probability of successful execution of a task within the given deadline. We develop the Markov chain model for a real-time task having the proposed checkpoints, and derive the optimal fault detection and checkpoint interval.

Online Checkpointing with Improved Worst-Case Guarantees

In the online checkpointing problem, the task is to continuously maintain a set of k checkpoints that allow rewinding an ongoing computation faster than by a full restart. The only operation allowed is to replace an old checkpoint by the current state. Our aim is checkpoint placement strategies that minimize rewinding cost, i.e., such that at all times T when requested to rewind to some time t ≤ T the number of computation steps that need to be redone to get to t from a checkpoint before t is as few as possible. In particular, we want the closest checkpoint earlier than t to be no farther away from t than qk times the ideal distance T/(k + 1), where qk is a small constant. Improving earlier work showing 1 + 1/k ≤ qk ≤ 2, we show that qk can be chosen asymptotically less than 2. We present algorithms with asymptotic discrepancy qk ≤ 1.59 + o(1) valid for all k and qk ≤ ln(4) + o(1) ≤ 1.39 + o(1) valid for k being a power of two. Experiments indicate the uniform bound pk ≤ 1.7 for all k. For small k, we show how to use a linear programming approach to compute good checkpointing algorithms. This gives discrepancies of less than 1.55 for all k < 60. We prove the first lower bound that is asymptotically more than 1, namely qk ≥ 1.30 − o(1). We also show that optimal algorithms (yielding the infimum discrepancy) exist for all k.

PROBLEMS OF QUALITY CONTROL DURING TRANSPORTATION OF PERISHABLE GOODS

Competition between different modes of transport requires the provision of delivery of perishable goods to consumers as soon as possible without loss and lowering quality. Therefore, in recent years, carriers are paying more attention to automation of the control of the perishable cargo during transportation. The traditional solution to the problem of temperature control in transport is, first of all, the use of stand-alone electronic recorders, which are discussed in the article. However, the application of these devices as monitors of the temperature and other parameters of isothermal space of vehicle implies the necessity of choosing an optimal placement of registrations or so-called checkpoints that require further research.

Static Analysis for the Placement of Application-Level Checkpoints on Heterogeneous System

Static Analysis for the Placement of Application-Level Checkpoints on Heterogeneous System

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.

Aperiodic Checkpoint Placement Algorithms—Survey and Comparison

In this article we summarize some aperiodic checkpoint placement algorithms for a software system over infinite and finite operation time horizons, and compare them in terms of computational accuracy. The underlying problem is formulated as the maximization of steady-state system availability and is to determine the optimal aperiodic checkpoint sequence. We present two exact computation algorithms in both forward and backward manners and two approximate ones; constant hazard approximation and fluid approximation, toward this end. In numerical examples with Weibull system failure time distribution, it is shown that the combined algorithm with the fluid approximation can calculate effectively the exact solutions on the optimal aperiodic checkpoint sequence.

Optimal Checkpoint Placement on Real-Time Tasks with Harmonic Periods

This paper presents an optimal checkpoint strategy for fault-tolerance in real-time systems where transient faults occur in Poisson distribution. In our environment, multiple real-time tasks with different deadlines and harmonic periods are scheduled in the system by rate-monotonic algorithm, and checkpoints are inserted at a constant interval in each task. When a fault is detected, the system carries out rollback to the latest checkpoint and re-executes tasks. The maximum number of re-executable checkpoints and an equation to check schedulability are derived, and the optimal number of checkpoints is selected to maximize the probability of completing all the tasks within their deadlines.

데드라인이 주기보다 긴 멀티 태스크를 가진 실시간 시스템을 위한 최적 체크포인트 배치

For a successful checkpointing strategy, we should place checkpoints so as to optimize fault-tolerance capability of real-time systems. This paper presents a novel scheme of checkpoint placement for real-time systems with periodic multi-tasks. Under the influence of transient faults, multi-tasks are scheduled by the Rate Monotonic (RM) algorithm. The optimal checkpoint intervals are derived to maximize the probability of task completion. In particular, this paper is concerned about the general case that the deadline of a task is longer than the period. Compared with the special condition that the deadline is equal to or less than the period, this general case causes a more complicate test procedure for schedulability of the RM algorithm with respect to a given set of checkpoint re-execution vectors. The probability of task completion is also derived in a more complex form. A case study is given to show the applicability of the proposed scheme.

Issues Involving the Placement of Watchmen Inside Early Modern Checkpoints : Particularly Concerning the Hakone Checkpoint

Issues Involving the Placement of Watchmen Inside Early Modern Checkpoints : Particularly Concerning the Hakone Checkpoint

Software Assistants for Randomized Patrol Planning for the LAX Airport Police and the Federal Air Marshal Service

The increasing threat of terrorism makes security at major locations of economic or political importance a major concern. Limited security resources prevent complete security coverage, allowing adversaries to observe and exploit patterns in patrolling or monitoring, and enabling them to plan attacks that avoid existing patrols. The use of randomized security policies that are more difficult for adversaries to predict and exploit can counter their surveillance capabilities. We describe two applications, ARMOR and IRIS, that assist security forces in randomizing their operations. These applications are based on fast algorithms for solving large instances of Bayesian Stackelberg games. Police at the Los Angeles International Airport deploy ARMOR to randomize the placement of checkpoints on roads entering the airport and the routes of canine unit patrols within the airport terminals. The Federal Air Marshal Service has deployed IRIS in a pilot program to randomize the schedules of air marshals on international flights. This paper examines the design choices, information, and evaluation criteria that were critical to developing these applications.

Complexity of Computing Optimal Stackelberg Strategies in Security Resource Allocation Games

Recently, algorithms for computing game-theoretic solutions have been deployed in real-world security applications, such as the placement of checkpoints and canine units at Los Angeles International Airport. These algorithms assume that the defender (security personnel) can commit to a mixed strategy, a so-called Stackelberg model. As pointed out by Kiekintveld et al. (2009), in these applications, generally, multiple resources need to be assigned to multiple targets, resulting in an exponential number of pure strategies for the defender. In this paper, we study how to compute optimal Stackelberg strategies in such games, showing that this can be done in polynomial time in some cases, and is NP-hard in others.

Design Optimization of Time- and Cost-Constrained Fault-Tolerant Embedded Systems With Checkpointing and Replication

We present an approach to the synthesis of fault-tolerant hard real-time systems for safety-critical applications. We use checkpointing with rollback recovery and active replication for tolerating transient faults. Processes and communications are statically scheduled. Our synthesis approach decides the assignment of fault-tolerance policies to processes, the optimal placement of checkpoints and the mapping of processes to processors such that multiple transient faults are tolerated and the timing constraints of the application are satisfied. We present several design optimization approaches which are able to find fault-tolerant implementations given a limited amount of resources. The developed algorithms are evaluated using extensive experiments, including a real-life example.

Numerical computation algorithms for sequential checkpoint placement

This paper concerns sequential checkpoint placement problems under two dependability measures: steady-state system availability and expected reward per unit time in the steady state. We develop numerical computation algorithms to determine the optimal checkpoint sequence, based on the classical Brender’s fixed point algorithm and further give three simple approximation methods. Numerical examples with the Weibull failure time distribution are devoted to illustrate quantitatively the overestimation and underestimation of the sub-optimal checkpoint sequences based on the approximation methods.

A DP-BASED CHECKPOINTING SCHEME IN REAL-TIME APPLICATIONS

In this paper, we consider computation algorithms for checkpoint placement in real-time applications. Under the condition that the processing time is bounded by a time limit, we derive sequentially the optimal checkpoint time based on the dynamic programming. In numerical examples, we examine the dependence of optimal checkpoint sequence on both failure time and processing time distributions, and investigate the effectiveness of sequential checkpoint placement.

Distribution-Free Checkpoint Placement Algorithms Based on Min-Max Principle

In this paper, we consider two kinds of sequential checkpoint placement problems with infinite/finite time horizon. For these problems, we apply approximation methods based on the variational principle and develop computation algorithms to derive the optimal checkpoint sequence approximately. Next, we focus on the situation where the knowledge on system failure is incomplete, i.e., the system failure time distribution is unknown. We develop the so-called min-max checkpoint placement methods to determine the optimal checkpoint sequence under an uncertain circumstance in terms of the system failure time distribution. In numerical examples, we investigate quantitatively the proposed distribution-free checkpoint placement methods, and refer to their potential applicability in practice.

The interplay of power management and fault recovery in real-time systems

We describe how to exploit the scheduling slack in a real-time system to reduce energy consumption and achieve fault tolerance at the same time. During failure-free operation, a task takes checkpoints to enable recovery from failure. Additionally, the system exploits the slack to conserve energy by reducing the processor speed. If a task fails, it will restart from a saved checkpoint and execute at maximum speed to guarantee that the deadlines are met. We show that the number of checkpoints and their placements interact in subtle ways with the power management policy. We study two checkpoint placement policies for aperiodic tasks and analytically derive the optimal number of checkpoints to conserve energy under each. This optimal number allows the CPU speed to be slowed down to the level that yields minimum energy consumption, while still guaranteeing recoverability of tasks under each checkpointing policy. The results show that traditional periodic checkpointing is not the best policy for the combined purpose of conserving energy and guaranteeing recovery. Instead, better energy savings are possible through a nonuniform distribution of checkpoints that takes into account the energy consumption and reliability factors. Depending on the amount of slack and the checkpointing overhead, energy can be reduced by up to 68 percent under nonuniform checkpointing. We also demonstrate the applicability of these checkpoint placement policies to periodic tasks.