Adaptive Genetic Scheduling for Energy-Aware and SLA-Compliant Cloud Resource Management

P U Anitha, K Ruth Isabels, M Ambika, C Dastagiraiah, Lokasani Bhanuprakash, Jagadesh J

2025

Abstract

An adaptive genetic algorithm (aGA) as an energy-aware scheduling approach for allocating resources in a manner that minimizes energy usage while meeting SLA in the cloud centers is presented in 8. Use real-time workload prediction, thermal-aware VM placement and cooling system optimization are combined into an integrated scheduling model, which is different from the conventional methods. The improved genetic strategy adaptively adjusts according to the varying workloads and conditions of infrastructure, and the results show that the virtual machine consolidation strategy can be achieved efficiently and does not deteriorate the performance. Comprehensive experiments on large datasets are conducted which shows clearly that the proposed algorithm has great advantage on energy conservation, fine resource allocation and QoS guarantee, which confirms the reliability and intelligence for sustainable Cloud management.

Paper Citation

in Harvard Style

Anitha P., Ruth Isabels K., Ambika M., Dastagiraiah C., Bhanuprakash L. and J J. (2025). Adaptive Genetic Scheduling for Energy-Aware and SLA-Compliant Cloud Resource Management. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 774-781. DOI: 10.5220/0013943500004919

in Bibtex Style

@conference{icrdicct`2525,
author={P U Anitha and K Ruth Isabels and M Ambika and C Dastagiraiah and Lokasani Bhanuprakash and Jagadesh J},
title={Adaptive Genetic Scheduling for Energy-Aware and SLA-Compliant Cloud Resource Management},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={774-781},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013943500004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Adaptive Genetic Scheduling for Energy-Aware and SLA-Compliant Cloud Resource Management
SN - 978-989-758-777-1
AU - Anitha P.
AU - Ruth Isabels K.
AU - Ambika M.
AU - Dastagiraiah C.
AU - Bhanuprakash L.
AU - J J.
PY - 2025
SP - 774
EP - 781
DO - 10.5220/0013943500004919
PB - SciTePress