Energy-Aware Task Scheduling and Resource Allocation in Cloud Computing
Authors
Yamina Mehor1, *, Mohammed Rebbah1, Omar Smail1
1LISYS Laboratory, Computer Science Department, University of Mustapha Stambouli Mascara, Mascara, Algeria
*Corresponding author.
Email: yamina.mehor@univ-mascara.dz
Corresponding Author
Yamina Mehor
Available Online 5 August 2025.
- DOI
- 10.2991/978-94-6463-805-9_29How to use a DOI?
- Keywords
- Cloud computing; energy usage; task scheduling; resource allocation
- Abstract
Cloud computing is essential for modern technology. Resource allocation and task scheduling are critical parts of cloud computing. A novel task scheduling and VM allocation (TSVMP) in cloud computing are proposed to reduce energy and resource consumption. Task scheduling and VM allocation compose the TSVMP. The simulation results indicate that TSVMP achieves improved overall results in terms of reducing the data center’s energy and resource consumption.
- Copyright
- © 2025 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
TY - CONF AU - Yamina Mehor AU - Mohammed Rebbah AU - Omar Smail PY - 2025 DA - 2025/08/05 TI - Energy-Aware Task Scheduling and Resource Allocation in Cloud Computing BT - Proceedings of the First International Conference on Artificial Intelligence, Smart Technologies and Communications (AISTC 2025) PB - Atlantis Press SP - 258 EP - 263 SN - 1951-6851 UR - https://doi.org/10.2991/978-94-6463-805-9_29 DO - 10.2991/978-94-6463-805-9_29 ID - Mehor2025 ER -