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A multi-objective crow search algorithm for optimizing makespan and costs in scientific cloud workflows (CSAMOMC).
- Source :
-
Computing . Jun2024, Vol. 106 Issue 6, p1777-1793. 17p. - Publication Year :
- 2024
-
Abstract
- Nowadays, with the rapid expansion of cloud computing technology in processing Internet of Things (IoT) workloads, the demand for data centers has significantly increased, leading to a surge in CO2 emissions, power consumption, and global warming. As a result, extensive research and initiatives have been undertaken to tackle this problem. Two specific approaches focus on enhancing workload scheduling, a complex problem known as NP-Hard, and integrating scheduling into scientific workflows. In this investigation, we present a multi-objective Crow Search Algorithm (CSA) for optimizing both makespan and costs in scientific cloud workflows (CSAMOMC). We conduct a comparative analysis between our approach and the well-known HEFT and TC3pop algorithms, which are commonly used for reducing makespan and optimizing costs. Our findings demonstrate that CSAMOMC is capable of achieving an average makespan reduction of 4.42% and a cost reduction of 4.77% when compared to the aforementioned algorithms. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 0010485X
- Volume :
- 106
- Issue :
- 6
- Database :
- Academic Search Index
- Journal :
- Computing
- Publication Type :
- Academic Journal
- Accession number :
- 177560432
- Full Text :
- https://doi.org/10.1007/s00607-024-01263-4