Design of Task Scheduling and Fault Tolerance Mechanism Based on GWO Algorithm for Attaining Better QoS in Cloud System

Indhumathi, R.; Amuthabala, K.; Kiruthiga, G.; Yuvaraj, N.; Pandey, Anand

doi:10.1007/s11277-022-10072-x

Cited by 16 publications

(2 citation statements)

References 23 publications

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“…Once an idle node is discovered, the algorithm calculates the threshold and fitness function for each node to ensure optimal load balancing. In Reference 105, authors introduced GWO algorithm and a fault detection method to execute and detects failed tasks respectively. The proposed work includes task scheduling with load balancing to acheive better quality of services.…”

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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“…To overcome workload issues, the task scheduling process is utilized. Indhumathi et al [20] proposed task execution implemented by GWO and demonstrated the superiority of the proposed method over traditional techniques.…”

Section: Scheduling Problemsmentioning

confidence: 99%

The Development and Application Research of Grey Wolf Optimization Algorithm

Chai,

Zhang,

Liu

2024

Frontiers in Artificial Intelligence and Applications

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The Grey Wolf Optimization (GWO) algorithm is an emerging swarm intelligence optimization technique known for its simplicity, minimal control parameters, fast convergence, and ease of implementation. This paper investigates the search mechanism and implementation process of the GWO algorithm, analyzing its shortcomings, including poor population diversity, slow convergence in later stages, and susceptibility to local optima. It provides an overview of improvement strategies for the Grey Wolf Optimization algorithm, encompassing enhancements to the population, parameters, search mechanism, and its integration with other optimization algorithms. Furthermore, the paper discusses the applications of the Grey Wolf Optimization algorithm in various domains.

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Fault-tolerant allocation of deadline-constrained tasks through preemptive migration in heterogeneous cloud environments

Kirti,

Maurya,

Yadav

2024

Cluster Comput

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Design of Task Scheduling and Fault Tolerance Mechanism Based on GWO Algorithm for Attaining Better QoS in Cloud System

Cited by 16 publications

References 23 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

The Development and Application Research of Grey Wolf Optimization Algorithm

Fault-tolerant allocation of deadline-constrained tasks through preemptive migration in heterogeneous cloud environments

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