Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)

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Task Scheduling Algorithms for Cloud Computing Resource Allocation: A Systematic Analysis Environment

Authors
G. B. Renuka1, S. Mohammed Sanauallah2, *, G. Sai Yadav2, A. Sukhdev Reddy2, K. Sasidhar2
1Assistant Professor, Department of CSE, Madanapalle Institute of Technology & Science Madanapalle, Madanapalle, Andhra Pradesh, India
2Final Year, Department of CSE, Madanapalle Institute of Technology & Science Madanapalle, Madanapalle, Andhra Pradesh, India
*Corresponding author. Email: smsanaullah@gmail.com
Corresponding Author
S. Mohammed Sanauallah
Available Online 30 July 2024.
DOI
10.2991/978-94-6463-471-6_50How to use a DOI?
Keywords
Task scheduling; Virtual machine; Cloud Computing Virtualization
Abstract

Task scheduling in cloud computing environments is crucial for optimizing resource allocation and enhancing system efficiency. In this paper, we present a systematic analysis environment for evaluating various task scheduling algorithms. We focus on three prominent algorithms: Ant Colony Optimization (ACO), Round Robin, and Genetic Algorithm (GA). Each algorithm offers unique strengths and trade-offs, making them suitable for different cloud computing scenarios. Firstly, we delve into the principles of Ant Colony Optimization, leveraging the collective intelligence of artificial ants to find optimal task assignments in a distributed manner. Secondly, Round Robin, a simple yet effective algorithm, cyclically allocates tasks among available resources, ensuring fair utilization. Lastly, Genetic Algorithm, inspired by natural selection processes, evolves task scheduling solutions over successive generations, adapting to dynamic workload conditions.

Copyright
© 2024 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 Computational Innovations and Emerging Trends (ICCIET- 2024)
Series
Advances in Computer Science Research
Publication Date
30 July 2024
ISBN
10.2991/978-94-6463-471-6_50
ISSN
2352-538X
DOI
10.2991/978-94-6463-471-6_50How to use a DOI?
Copyright
© 2024 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  - G. B. Renuka
AU  - S. Mohammed Sanauallah
AU  - G. Sai Yadav
AU  - A. Sukhdev Reddy
AU  - K. Sasidhar
PY  - 2024
DA  - 2024/07/30
TI  - Task Scheduling Algorithms for Cloud Computing Resource Allocation: A Systematic Analysis Environment
BT  - Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)
PB  - Atlantis Press
SP  - 518
EP  - 528
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-471-6_50
DO  - 10.2991/978-94-6463-471-6_50
ID  - Renuka2024
ER  -