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DOI: 10.14569/IJACSA.2021.0120646
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Cost Effective Hybrid Fault Tolerant Scheduling Model for Cloud Computing Environment

Author 1: Annabathula. Phani Sheetal
Author 2: K. Ravindranath

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 6, 2021.

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Abstract: Cloud computing provides flexible and cost effective way for end users to access data from multiplatform environment. Despite of support by the features of cloud computing, there are also chances of resource failure. Hence there is a need of a fault tolerant mechanism to achieve undisrupted performance of cloud services. The task reallocation and duplication are the two commonly used fault tolerant mechanisms. But task replication method results in huge storage and computational overhead, when the number of tasks is increasing gradually. If the number of faults are high, it incurs more storage overhead and time complexity based on task criticality. In order to solve these issues, we propose to develop a Cost Effective Hybrid Fault Tolerant Scheduling (CEHFTS) Model for cloud computing. In this model, the Failure Occurrence Probability (FoP) of each VM is estimated by finding the previous failures and successful executions. Then an adaptive fault recovery timer is maintained during a fault, which is adjusted based on the type of faults. Experimental results have shown that CEHFTS model achieves 43% reduced storage cost and 13% reduced response delay for critical tasks, when compared to existing technique.

Keywords: Cloud computing; failures; fault tolerant; critical tasks; scheduling; fault recovery; overhead

Annabathula. Phani Sheetal and K. Ravindranath, “Cost Effective Hybrid Fault Tolerant Scheduling Model for Cloud Computing Environment” International Journal of Advanced Computer Science and Applications(IJACSA), 12(6), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120646

@article{Sheetal2021,
title = {Cost Effective Hybrid Fault Tolerant Scheduling Model for Cloud Computing Environment},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120646},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120646},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {6},
author = {Annabathula. Phani Sheetal and K. Ravindranath}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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