Line: Evaluating Software Applications in Unreliable Environments
- Submitting institution
-
Imperial College of Science, Technology and Medicine
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2287
- Type
- D - Journal article
- DOI
-
10.1109/TR.2017.2655505
- Title of journal
- IEEE Transactions on Reliability
- Article number
- -
- First page
- 837
- Volume
- 66
- Issue
- 3
- ISSN
- 1558-1721
- Open access status
- Compliant
- Month of publication
- February
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
10.1109/TR.2017.2655505
- 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
-
1
- Research group(s)
-
-
- Citation count
- 5
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Unreliability and time-varying behaviour of cloud resources make it challenging to design software systems that take performance requirements into account. The open-source LINE solver (http://line-solver.sf.net; >570 downloads) supports rigorous performance evaluation for such applications, efficiently computing probabilistic measures essential to assess service-level agreement compliance. The solver has been integrated into the MODAClouds platform (http://multiclouddevops.com/byproducts.html#MODACloudsForPalladio) and Palladio Bench 4.0 by KIT Germany (https://www.palladio-simulator.com/science/references/). LINE received follow-on funding from EPSRC (EP/M009211/1) and H2020 (DICE 644869, RADON 825040) that led to a new release (2.0), awarded the Best Demo at ACM/SPEC ICPE’19. Extensions done with U. Nottingham appeared in Elsevier PEVA (https://doi.org/10.1016/j.peva.2020.102094).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
