Modeling the Gradual Degradation of Eventually-Consistent Distributed Graph Databases
- Submitting institution
-
University of Newcastle upon Tyne
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 270355-66266-1292
- Type
- D - Journal article
- DOI
-
-
- Title of journal
- Queueing Models and Service Management
- Article number
- -
- First page
- 235
- Volume
- 3
- Issue
- 2
- ISSN
- 2616-2679
- Open access status
- Compliant
- Month of publication
- September
- Year of publication
- 2020
- URL
-
http://qmsm.pu.edu.tw/papers/paper/QMSM-2020-6-04_corrected_proof.pdf
- 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
-
2
- Research group(s)
-
D - Scalable Computing
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This output presents work which is the first in offering an accurate quantitative assessment of the damage that the eventually consistent update policy can inflict on a distributed graph database. The paper results from a collaboration with Neo4j - the world-leading graph database company (the third author is Neo4j's Chief Scientist). This work builds on an earlier paper that was presented at the international EPEW’18 conference and includes a new solution method, together with applications to databases which are an order of magnitude larger than those tackled before.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -