A Comparison of Application-Level Fault Tolerance Schemes for Task Pools

Posner, Jonas; Reitz, Lukas; Fohry, Claudia

doi:10.1016/j.future.2019.11.031

Cited by 13 publications

(15 citation statements)

References 17 publications

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“…We refer to the AllFT algorithm from Posner et al [8], which is the simplest of three DIT algorithms suggested in that reference. Our techniques may extend to their incremental scheme, which reduces the overhead for large task descriptors.…”

Section: Checkpointing Algorithmmentioning

confidence: 99%

“…A few localized, and partly shrinking, recovery techniques have already been suggested, notably in the context of taskbased parallel programming [6]- [8]. This context is generally promising for the provision of resilience: Since tasks have clearly defined interfaces, checkpointing at the task level allows to nicely combine ease-of-use and efficiency.…”

Section: Introductionmentioning

confidence: 99%

“…Checkpointing algorithms already exist for other classes of task-based parallel programs [6], [20]. We refer to an algorithm for dynamic independent tasks (DIT) from Posner et al [8], and adapt it to NFJ. Like NFJ tasks, DIT tasks are spawn dynamically, forming a tree.…”

Section: Introductionmentioning

confidence: 99%

“…A recent study has compared the algorithms from Kestor et al [7] and Posner et al [8] in DIT, to which the NFJ algorithm was transferred [21]. The study reported overheads below 1% for both algorithms, with those of the NFJ-specific algorithm [7] being lower in failure-free cases, and those of the checkpointing algorithm [8] being lower during recovery. We expect similar results for NFJ, since the algorithm proposed in this paper closely resembles the original one.…”

Section: Introductionmentioning

confidence: 99%

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Checkpointing and Localized Recovery for Nested Fork-Join Programs

Fohry

2021

Preprint

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While checkpointing is typically combined with a restart of the whole application, localized recovery permits all but the affected processes to continue. In task-based cluster programming, for instance, the application can then be finished on the intact nodes, and the lost tasks be reassigned.This extended abstract suggests to adapt a checkpointing and localized recovery technique that has originally been developed for independent tasks to nested fork-join programs. We consider a Cilk-like work stealing scheme with work-first policy in a distributed memory setting, and describe the required algorithmic changes. The original technique has checkpointing overheads below 1% and neglectable costs for recovery, we expect the new algorithm to achieve a similar performance.

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Section: Checkpointing Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Checkpointing and Localized Recovery for Nested Fork-Join Programs

Fohry

2021

Preprint

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“…The current methods address both load balancing and fault tolerance in grid environments separately [ 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 ]. The method proposed in this paper deals with each of them within one framework by combining some classical methods based on fractal transform and entropy computation for reducing the complexity of data to obtain an optimal method for rendering the grid structure.…”

Section: Related Workmentioning

confidence: 99%

The Application of Fractal Transform and Entropy for Improving Fault Tolerance and Load Balancing in Grid Computing Environments

Khorsheed

Zainel

Hassen

et al. 2020

Entropy

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This paper applies the entropy-based fractal indexing scheme that enables the grid environment for fast indexing and querying. It addresses the issue of fault tolerance and load balancing-based fractal management to make computational grids more effective and reliable. A fractal dimension of a cloud of points gives an estimate of the intrinsic dimensionality of the data in that space. The main drawback of this technique is the long computing time. The main contribution of the suggested work is to investigate the effect of fractal transform by adding R-tree index structure-based entropy to existing grid computing models to obtain a balanced infrastructure with minimal fault. In this regard, the presented work is going to extend the commonly scheduling algorithms that are built based on the physical grid structure to a reduced logical network. The objective of this logical network is to reduce the searching in the grid paths according to arrival time rate and path’s bandwidth with respect to load balance and fault tolerance, respectively. Furthermore, an optimization searching technique is utilized to enhance the grid performance by investigating the optimum number of nodes extracted from the logical grid. The experimental results indicated that the proposed model has better execution time, throughput, makespan, latency, load balancing, and success rate.

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Proactive self‐healing techniques for cloud computing: A systematic review

Rouholamini,

Mirabi,

Farazkish

et al. 2024

Concurrency and Computation

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SummaryEnsuring the seamless operation of cloud computing services is paramount for meeting user demands and ensuring business continuity. Fault‐tolerant self‐healing techniques play a crucial role in enhancing the reliability and availability of cloud platforms, minimizing downtime and ensuring uninterrupted service delivery. This article systematically categorizes and analyzes existing research on fault‐tolerant self‐healing techniques published between 2005 and 2024. We provide a comprehensive technical taxonomy organizing self‐healing techniques based on fault tolerance processes, encompassing considerations for both reliability and availability. Additionally, we evaluate applications of proactive self‐healing techniques, highlighting their achievements, and limitations in enhancing service continuity. Strategies to address identified weaknesses are discussed, alongside future research challenges and open issues in the domain of cloud resilience. Through this analysis, the article contributes to understanding self‐healing techniques in cloud computing, offering insights into their effectiveness in ensuring service continuity. The findings aim to guide future research efforts in developing more robust and resilient cloud infrastructures, ultimately enhancing overall service reliability and availability. By emphasizing the importance of fault tolerance and self‐healing techniques, this article lays the foundation for advancing the state‐of‐the‐art in cloud computing.

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A Comparison of Application-Level Fault Tolerance Schemes for Task Pools

Cited by 13 publications

References 17 publications

Checkpointing and Localized Recovery for Nested Fork-Join Programs

Checkpointing and Localized Recovery for Nested Fork-Join Programs

The Application of Fractal Transform and Entropy for Improving Fault Tolerance and Load Balancing in Grid Computing Environments

Proactive self‐healing techniques for cloud computing: A systematic review

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