Extending Science Gateway Frameworks to Support Big Data Applications in the Cloud
- Submitting institution
-
The University of Westminster
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 9wy44
- Type
- D - Journal article
- DOI
-
10.1007/s10723-016-9369-8
- Title of journal
- Journal of Grid Computing
- Article number
- -
- First page
- 589
- Volume
- 14
- Issue
- 4
- ISSN
- 1570-7873
- Open access status
- Compliant
- Month of publication
- June
- Year of publication
- 2016
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
3
- Research group(s)
-
-
- Citation count
- 6
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper suggests a generic approach and provides a reference implementation and experimental evaluation for the extension of science gateway frameworks with Big Data processing capabilities, based on the concept of infrastructure aware workflows. The paper is significant as the suggested approach enables science gateway developers to integrate Big Data processing into their gateways and offer such solutions to a wide variety of end users. Based on the concept described in the paper, a WS-PGRADE portal, integrated with Hadoop services has been implemented and offered as a service to users of the European Grid Infrastructure’s (EGI) Federated Cloud (https://wiki.egi.eu/wiki/ServiceGuides).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
