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Development of a new task scheduling in cloud computing

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Abstract

Several toolkits are in use to execute cloud applications for technology development. Workflow Sim Toolkit is one of them. It captures the flow of work in a systematic manner and carries out the technical work successfully. To represent and apply the technology, the researchers raised the cloud. For processing technical tasks, cloud service is sustainable to operate with ease of delivery. With dynamic requirements mapping the available resources to ensure tremendous performance, cloud comes into play. By proposing descriptive steps of an algorithm, advanced architecture is able to solve real dynamic complex technical task applications. The suggested architecture is implemented in a real environment with the mentioned toolkit. The proposed architecture is evaluated using the existing work request and Amazon EC2 pricing model. This model gained attention for the most commonly used application by incorporating previous implemented models to predict accuracy in results with actual platform comparisons. In the experimental results of the designed paper, the Approachable Algorithm (AA) got better performance than the basic algorithms i.e. FCFS, RR, MIN-MIN, MAX–MIN and HoneyBees.

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Acknowledgements

The authors would like to indicate their special thanks and gratitude to computer science and engineering department of Sharda University Greater Noida for providing all technical support. The authors also thank the anonymous reviewers forgiving their valuable comments and helping us to improve the quality of the paper.

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NB wrote the manuscript and designed the graphs. AKS read and approved the manuscript.

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Correspondence to Nidhi Bansal.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the University. All applicable international, national, and/or institutional guidelines for the care and use of animals were followed.

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Bansal, N., Singh, A.K. Development of a new task scheduling in cloud computing. Int J Syst Assur Eng Manag 14, 2267–2275 (2023). https://doi.org/10.1007/s13198-023-02068-y

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  • DOI: https://doi.org/10.1007/s13198-023-02068-y

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