Name
Abstract | ||
|---|---|---|
Reliability is one of the key concerns of both cloud providers and consumers, who require accurate reliability evaluation methods to develop, deploy, and maintain cloud applications. However, few works assess the reliability of cloud applications considering deep dependencies in the deployment stack. To explore the impact of deep dependencies to the reliability assessment, in this paper, we propose a layered dependency graph-based reliability assessment method for cloud applications. By introducing the inner reliability of cloud components, and combining the deep dependencies between services and physical servers, the method can assess the reliability of all components as well as the application. We implement a framework for the method and compare the assessment results of our approach against existing methods. The results show that deep dependencies have few impacts on the accuracy while can improve the precision of reliability assessment methods because the failure rate of physical servers is much lower than software components. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/CLOUD.2017.73 | 2017 IEEE 10th International Conference on Cloud Computing (CLOUD) |
Keywords | Field | DocType |
cloud application,reliability assessment,dependencies | Software deployment,Computer science,Server,Failure rate,Real-time computing,Redundancy (engineering),Component-based software engineering,Software quality,Dependency graph,Reliability engineering,Cloud computing,Distributed computing | Conference |
ISSN | ISBN | Citations |
2159-6182 | 978-1-5386-1994-0 | 0 |
PageRank | References | Authors |
0.34 | 16 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiao-Wei Wang | 1 | 596 | 59.78 |
| Fabian Glaser | 2 | 2 | 1.07 |
| Steffen Herbold | 3 | 129 | 18.49 |
| Jens Grabowski | 4 | 618 | 73.49 |