Dynamic Replication Policy on HDFS Based on Machine Learning Clustering

Ahmed, Motaz A.; Khafagy, Mohamed Helmy; Shaheen, Masoud E.; Kaseb, Mostafa R.

doi:10.1109/access.2023.3247190

Cited by 4 publications

(1 citation statement)

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“…They implemented a heuristic model that uses restore techniques and checkpoints, supported by a statistical model that predicts the revocation time by defining the best checkpoint interval and scrutinizing the price change. Ahmed et al 139 integrates reactive fault tolerance approaches, that is, replication with adaptive such that machine learning to minimize storage usage, optimize read and write operations, and maintain the availability and reliability of the system. The paper uses machine learning to cluster groups and applied dynamic replication policy on each group to enhance their availability.…”

Section: Taxonomy Of Fault Tolerance Approachesmentioning

confidence: 99%

Fault‐tolerance approaches for distributed and cloud computing environments: A systematic review, taxonomy and future directions

Kirti,

Maurya,

Yadav

2024

Concurrency and Computation

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Fault tolerance is crucial in ensuring smooth working of distributed and cloud computing. It is challenging to implement because of the constantly changing infrastructure and complex configurations in distributed and cloud computing. Implementation of various fault tolerance methods require domain‐specific knowledge as well as in‐depth understanding of the existing techniques and approaches. Recent surveys on fault tolerance in cloud and distributed environments exist, but they have limitations. This article systematically reviews fault tolerance approaches in distributed and cloud computing and discusses their taxonomy. Based on the taxonomy provided, fault‐tolerance approaches are divided into four types, that is, reactive approaches, proactive approaches, adaptive approaches, and hybrid approaches. Reactive approaches provide a preventive measure after the occurrence of faults in the system. Proactive approaches prevent the system or minimize failure effects by predicting in advance. The adaptive approaches predict, learn, and adapt the changes to deal with new faults in the system. The hybrid approaches combine reactive, proactive, and adaptive approaches. The objective of this article is to give a better understanding of handling faults using suitable approaches and further compare them on various parameters. The paper also presents a promising research direction based on the challenges and issues in multiple approaches.

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Section: Taxonomy Of Fault Tolerance Approachesmentioning

confidence: 99%