Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)

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Multi Objective Ameliorated Repetitive Resource Allocation Algorithm for Cloud Resource Scheduling and Allocation

Authors
Dipa D. Dharmadhikari1, *, Sharvari Chandrashekhar Tamane2
1Department of CS and IT, Dr. Babasaheb Ambedkar, Marathwada University Aurangabad, Aurangabad, India
2MGM’s Jawaharlal Nehru Engineering College MGM University, Aurangabad, India
*Corresponding author. Email: dharmadhikari2021@gmail.com
Corresponding Author
Dipa D. Dharmadhikari
Available Online 1 May 2023.
DOI
10.2991/978-94-6463-136-4_34How to use a DOI?
Keywords
Resource Allocation; Task Scheduling; Cloud Computing
Abstract

Mapping huge jobs onto cloud resources is a part of workflow scheduling, which increases scheduling effectiveness. Numerous researchers have been working hard to enhance the efficiency of scheduling in cloud computing as a result of this piqued interest. Scientific workflows, on the other hand, are huge data applications, therefore the executions are costly and time-consuming. Thus, a novel Multi Objective Ameliorated Repetitive Resource Allocation Algorithm that can quickly respond to unforeseen needs has been proposed in order to enhance the system's efficiency in allocating work tasks. Resource performance and resource proportion matching distances are also established in order to achieve resource optimization and the balanced use of all available resources. The results of the simulation show that the suggested method can efficiently complete Virtual Machine (VM) allocation and deployment and well manage incoming streaming workloads with a random arriving rate. Compared to small and medium workflow jobs, the suggested algorithm performs much better in big and extra-large workflow tasks. The experimental findings demonstrate that our algorithm is capable of balancing the consumption of all types of resources while allocating resources swiftly and optimally for unexpected demands.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)
Series
Advances in Computer Science Research
Publication Date
1 May 2023
ISBN
10.2991/978-94-6463-136-4_34
ISSN
2352-538X
DOI
10.2991/978-94-6463-136-4_34How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Dipa D. Dharmadhikari
AU  - Sharvari Chandrashekhar Tamane
PY  - 2023
DA  - 2023/05/01
TI  - Multi Objective Ameliorated Repetitive Resource Allocation Algorithm for Cloud Resource Scheduling and Allocation
BT  - Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)
PB  - Atlantis Press
SP  - 403
EP  - 414
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-136-4_34
DO  - 10.2991/978-94-6463-136-4_34
ID  - Dharmadhikari2023
ER  -