Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{165886,
        author = {Vikrant Prasad and Mr. Shivam Shukla},
        title = {Review of An Energy Efficient Task Scheduling Algorithm In Cloud},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {1},
        pages = {2127-2135},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=165886},
        abstract = {Efficient task scheduling in cloud computing environments are crucial for optimizing resource utilization and minimizing energy consumption. This review explores recent advancements in energy-efficient task scheduling algorithms for cloud environments. The focus is on algorithms designed to minimize energy consumption while meeting performance requirements and ensuring fairness among tasks. Various approaches, including heuristic-based algorithms, genetic algorithms, and machine learning-based techniques, are discussed, highlighting their strengths and weaknesses. Additionally, challenges and future research directions in this domain are identified to provide insights for further advancements in energy-efficient task scheduling in cloud computing.},
        keywords = {Task scheduling, cloud computing, energy-efficient, genetic algorithms, machine learning.},
        month = {June},
        }