Name
Abstract | ||
|---|---|---|
The adoption of Cloud computing in the Service Oriented Architecture SOA world is continuously increasing. However, as developers try to optimize their application deployment cost and performance, they may also deploy application parts redundantly on different VMs. In such heterogeneous and distributed environments, it is important to have a clear view of the system's state and its components' interrelationships. This paper aims at proposing a novel monitoring and adaptation framework for Service-based Applications SBAs deployed on multiple Clouds. The main functionality of this framework is the discovery of critical event patterns within monitoring event streams, leading to specific Service Level Objective SLO violations. Furthermore, two main meta-models are proposed for describing the SBA's components and their dependencies, and the supported adaptation actions in a specific context respectively. The proposed approach is empirically evaluated based on a real-world traffic management application. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.4018/IJSSOE.2015100104 | IJSSOE |
Field | DocType | Volume |
Data mining,Service level objective,Software deployment,Service based applications,Computer science,GNSS augmentation,Service-oriented architecture,Cloud computing | Journal | 5 |
Issue | Citations | PageRank |
4 | 2 | 0.38 |
References | Authors | |
12 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chrysostomos Zeginis | 1 | 53 | 6.57 |
| Kyriakos Kritikos | 2 | 595 | 42.10 |
| Dimitris Plexousakis | 3 | 2586 | 326.38 |