Mobile Agents-Based Framework for Dynamic Resource Allocation in Cloud Computing

Safia Rabaaoui, Héla Hachicha, Héla Hachicha, Ezzeddine Zagrouba

2024

Abstract

Nowadays, cloud computing is becoming the more popular technology for various companies and consumers, who benefit from its increased efficiency, cost optimization, data security, unlimited storage capacity, etc. One of the biggest challenges of cloud computing is resource allocation. Its efficiency directly influences the performance of the whole cloud environment. Finding an effective method to address these critical issues and increase cloud performance was necessary. This paper proposes a mobile agents-based framework for dynamic resource allocation in cloud computing to minimize the cost of virtual machines and the makespan. Furthermore, its impact on the best response time and task rejection rate has been studied. The simulation shows that our method gave better results than the former ones.

Paper Citation

in Harvard Style

Rabaaoui S., Hachicha H. and Zagrouba E. (2024). Mobile Agents-Based Framework for Dynamic Resource Allocation in Cloud Computing. In Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-680-4, SciTePress, pages 766-773. DOI: 10.5220/0012390200003636

in Bibtex Style

@conference{icaart24,
author={Safia Rabaaoui and Héla Hachicha and Ezzeddine Zagrouba},
title={Mobile Agents-Based Framework for Dynamic Resource Allocation in Cloud Computing},
booktitle={Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2024},
pages={766-773},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012390200003636},
isbn={978-989-758-680-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Mobile Agents-Based Framework for Dynamic Resource Allocation in Cloud Computing
SN - 978-989-758-680-4
AU - Rabaaoui S.
AU - Hachicha H.
AU - Zagrouba E.
PY - 2024
SP - 766
EP - 773
DO - 10.5220/0012390200003636
PB - SciTePress