Name
Abstract | ||
|---|---|---|
Cloud computing emerged as a paradigm offering new benefits to both social networking and IT business. However, to keep up with the increasing workload demand and to ensure that their services will be provided in a fail-safe manner and under consideration of their service-level agreement, contemporary cloud platforms need to be autonomous and self-adaptive. The development of self-adaptive clouds is a very challenging task, which is mainly due to their non-deterministic behavior, driven by service-level objectives that must be achieved despite the dynamic changes in the cloud environment. This paper presents a formal approach to modeling self-adaptive behavior for clouds. The approach relies on the KnowLang language, a formal language dedicated to knowledge representation for self-adaptive systems. A case study is presented to demonstrate the formalization of Science Clouds, a special class of self-adaptive clouds providing a cloud-scientific platform. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-662-45234-9_9 | ISoLA (1) |
Field | DocType | Volume |
Data science,Knowledge representation and reasoning,Social network,Formal language,Workload,Computer science,Self adaptive,Cloud computing,Distributed computing | Conference | 8802 |
ISSN | Citations | PageRank |
0302-9743 | 1 | 0.39 |
References | Authors | |
5 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Emil Vassev | 1 | 263 | 41.81 |
| Mike Hinchey | 2 | 494 | 51.89 |
| Philip Mayer | 3 | 234 | 15.64 |