Advancing Cloud Task Scheduling: Recent Developments and Comparative Insights

Abstract

In the present landscape of cloud computing, the effective scheduling of tasks stands as a pivotal element in optimizing the operational efficiency of distributed systems. This paper conducts a thorough and comparative examination of recent trends and progress within this vital and ever-evolving domain. By meticulously reviewing crucial performance metrics and critically analyzing state-of-the-art methodologies, we present a comprehensive overview of Cloud Task Scheduling. We emphasize the shift towards multi-objective strategies, mirroring the escalating complexity and diversity witnessed in cloud environments.Employing innovative approaches and illustrative case studies, we delve into the practical implementation of prominent algorithms, including 𝐿𝐴𝐵𝐶, MaOEA-SIN, and MALO. The detailed analysis not only underscores their efficacy in real-world contexts but also pinpoints areas ripe for enhancement and adaptation within multi-cloud settings.Beyond offering an in-depth understanding of the latest developments in Cloud Task Scheduling, this article endeavors to stimulate collaboration and discourse within the academic and professional community. We aim to ignite future advancements, thereby contributing to the sustained growth of this strategic and dynamic field.