A meta synthesis on cloud task scheduling algorithms: COVID-19 and onwards

Aksöz, Ata Hüseyin
This thesis seeks to analyze different task scheduling algorithms proposed for Cloud Computing field and categorize such algorithms for different use cases. It is hypothesized that COVID-19 pandemic had huge impact on Cloud Computing field. The pandemic has shown that current Cloud Computing infrastructure is inferior as most business processes transferred to the Cloud and the network traffic increased. The research focuses on meta-synthesis of cloud task scheduling algorithms proposed during COVID-19 pandemic. How the pandemic has affected the design concerns is investigated. Narrative synthesis and thematic analysis of these algorithms in terms of their capabilities, performance, advantages and disadvantages are also done. It is known that efficient task scheduling is an issue. This issue has gained attention of lots of researchers who have proposed new algorithms or at least a variant of traditional scheduling algorithms. When those works are reviewed, it is seen that each algorithm has its pros and cons. Currently there is no such algorithm that can become the standard for task scheduling in Cloud Computing. This current situation in the field proves that there is a need for a meta synthesis of proposed algorithm. Hopefully this study will enlighten the Cloud Computing field for upcoming researchers. The aim of this thesis is to review state of the art algorithms and investigate how COVID-19 pandemic has affected design concerns of such algorithms. The final aim is to end up with a work that can be used as a starting point for many new researchers.
Citation Formats
A. H. Aksöz, “A meta synthesis on cloud task scheduling algorithms: COVID-19 and onwards,” M.S. - Master of Science, Middle East Technical University, 2024.