A hybrid bi-objective scheduling algorithm for execution of scientific workflows on cloud platforms with execution time and reliability approach
Author:
Publisher
Springer Science and Business Media LLC
Subject
Hardware and Architecture,Information Systems,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s11227-022-04703-0.pdf
Reference49 articles.
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2. Przybylski B (2021) Parallel-machine scheduling of jobs with mixed job-, machine- and position-dependent processing times. J Comb Optim. https://doi.org/10.1007/s10878-021-00821-2
3. Konjaang JK, Xu L (2021) Multi-objective workflow optimization strategy (MOWOS) for cloud computing. J Cloud Comput 10:11. https://doi.org/10.1186/s13677-020-00219-1
4. Zhou X, Wang H, Ding B, Hu T, Shang S (2018) Balanced connected task allocations for multi-robot systems: an exact ßow-based integer program and an approximate tree-based genetic algorithm. Expert Syst Appl. https://doi.org/10.1016/j.eswa.2018.09.001
5. Hosseini Shirvani M (2020) A hybrid meta-heuristic algorithm for scientific workflow scheduling in heterogeneous distributed computing systems. Eng Appl Artif Intell 90:103501. https://doi.org/10.1016/j.engappai.2020.103501
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