
The numerous heterogeneities among different providers make platform as a service interoperability an interesting and complex research and practical problem. For example, each provider offers its own remote application programming interfaces (APIs). The main aim of this paper is to identify and address service- level interoperability issues when using APIs from different commercial providers of platform as a service. First, we define use case to add current user information from one platform as a service offer to the application hosted on another offer. To address interoperability problems, the ontology driven data mediation will be used and tested in this use case. Remote vendors’ APIs are implemented as web services. Resulting web operations and their inputs/outputs are semantically annotated using cross-PaaS concepts from the developed platform as a service OWL ontology. Next, SAWSDL and XSLT are used to define service type mappings. Actual composition of platform as a service APIs is implemented by means of AI planner and developed Java web application. Testing and validation was performed on a case where current Salesforce’s user is added to data container in Vosao content management system deployed on Google App Engine. Novelty of the paper is a specific application domain (composition of operations defined in PaaS APIs) and new algorithm for identification of interoperability problems.
platform as a service ; interoperability ; service composition ; cloud APIs ; ontology driven mediation
platform as a service ; interoperability ; service composition ; cloud APIs ; ontology driven mediation
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 16 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
