On the Use of Cloud Computing for Scientific Workflows
By C. Hoffa, Gaurang Mehta, T. Freeman, Ewa Deelman, K. Keahey, B. Berriman, John Good. 2008 IEEE Fourth International Conference on eScience, 2008
408 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Information Systems, Information Systems and Management
View Paper: https://www.semanticscholar.org/paper/df4cce66d5779acbbd79def06db406a31d9d2c7d
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Ewa Deelman
- Gideon Juve
- Gaurang Mehta
- Karan Vahi
- Robert X. Gao
- Antonio Puliafito
- Ann L. Chervenak
- Rajkumar Buyya
In Information Systems
- Maria Fazio
- Ewa Deelman
- Antonio Puliafito
- Karan Vahi
- Soundar Kumara *
- Antonio Celesti
- Massimo Villari
- Gaurang Mehta
In Information Systems and Management
Citations in the corpus
- Cloud-enabled prognosis for manufacturing (2015, background): “Previous studies [207-208] have demonstrated the power of cloud computing on executing multi-task work.”
- Characterizing and profiling scientific workflows (2013, methodology): “The characterization is based on novel workflow profiling tools that provide detailed information about the various computational tasks that are present in the workflow.”
- How to Enhance Cloud Architectures to Enable Cross-Federation: Towards Interoperable Storage Providers (2010, methodology): “Considering the open source projects we distinguish two main categories: Low-Level Management, including projects such as OpenQRM [6] and OpenNebula [7], and High-Level Management including Nimbus [8], Eucalyptus [9].”
- A data placement strategy in scientific cloud workflows (2010, neutral): “[14] shows that cloud computing offers a cost-effective solution for data-intensive applications, such as scientific workflows [15].”