Fault Tolerance Using Self-Healing Sla and Load Balanced Dynamic Resource Provisioning in Cloud Computing

Sohani, Mayank; Jain, Sushma

doi:10.5455/jjcit.71-1620904727

Cited by 3 publications

(2 citation statements)

References 25 publications

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“…Support vector machines are supervised learning models with associated learning algorithms that analyze data used for classification and regression analysis. In Reference 112, authors addressed Predictive Cloud Computing Systems which focuses on predicting and handling unexpected failures through self‐healing methods. In this paper, workload is predicted based on current workload traces and the forecasted workload is utilized.…”

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%

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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“…Distributed computer selection is the idle computer selection in the cloud computing services management process, such as server selection [9], logical computer selection, transmission mode selection, cloud processing platform selection, and auxiliary computing selection.…”

Section: Selection Of Distributed Computersmentioning

confidence: 99%

An Empirical Study on Machine Learning for Enterprise Cloud Computing Service Management

Liu

2023

AJEBA

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A machine learning method is proposed to aim at the problems of large data processing, complex data, and limited system resources in cloud computing service management. First, multi-department analysis is carried out on cloud service management data, and relevant management data is standardized to form a standardized management data collection; Machine learning is used to classify, mine, and extract service management data, and corresponding management measures are taken promptly to improve the management level of cloud computing services. MATLAB simulation shows that machine learning can improve the level of cloud computing service management, simplify the process of cloud computing service management, shorten the management time of cloud computing services, and meet the actual needs of service management.

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Meta Heuristic Backtracking Algorithm for Virtual Machine Placement in Cloud Computing Migration

Suja

Booba

2022

Communications in Computer and Information Science

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Fault Tolerance Using Self-Healing Sla and Load Balanced Dynamic Resource Provisioning in Cloud Computing

Cited by 3 publications

References 25 publications

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

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

An Empirical Study on Machine Learning for Enterprise Cloud Computing Service Management

Meta Heuristic Backtracking Algorithm for Virtual Machine Placement in Cloud Computing Migration

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