| Autor: |
LIU Zhang-hui, ZHAO Xu, LIN Bing, CHEN Xing |
| Jazyk: |
čínština |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
Jisuanji kexue, Vol 48, Iss 11, Pp 199-207 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
1002-137X |
| DOI: |
10.11896/jsjkx.200900009 |
| Popis: |
A reasonable data placement strategy is essential to the efficient execution of scientific workflow in hybrid cloud environment.The traditional data placement strategy mainly focuses on the deterministic environment,but the data transmission time is uncertain due to the different load,bandwidth fluctuation and network congestion between different data centers and computer characteristics in the actual network environment.To solve this problem,a fuzzy adaptive discrete particle swarm optimization algorithm based on the fuzzy theory and genetic algorithm operator (FGA-DPSO) is proposed to minimize the fuzzy transmission time of data,place the scientific workflow data reasonably and meet the privacy requirements of the data set and the capacity limit of the data center.The experimental results show that the algorithm can effectively reduce the fuzzy data transmission time of scientific workflow in hybrid cloud environment. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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