31,459 research outputs found
Migrating medical communications software to a multi-tenant cloud environment
The rise of cloud computing has paved the way for many new applications. Many of these new cloud applications are also multi-tenant, ensuring multiple end users can make use of the same application instance. While these technologies make it possible to create many new applications, many legacy applications can also benefit from the added flexibility and cost-savings of cloud computing and multi-tenancy. In this paper, we describe the steps required to migrate a. NET-based medical communications application to the Windows Azure public cloud environment, and the steps required to add multi-tenancy to the application. We then discuss the advantages and disadvantages of our migration approach. We found that the migration to the cloud itself requires only a limited amount of changes to the application, but that this also limited the benefits, as individual instances would only be partially used. Adding multi-tenancy requires more changes, but when this is done, it has the potential to greatly reduce the cost of running the application
Towards Analytics Aware Ontology Based Access to Static and Streaming Data (Extended Version)
Real-time analytics that requires integration and aggregation of
heterogeneous and distributed streaming and static data is a typical task in
many industrial scenarios such as diagnostics of turbines in Siemens. OBDA
approach has a great potential to facilitate such tasks; however, it has a
number of limitations in dealing with analytics that restrict its use in
important industrial applications. Based on our experience with Siemens, we
argue that in order to overcome those limitations OBDA should be extended and
become analytics, source, and cost aware. In this work we propose such an
extension. In particular, we propose an ontology, mapping, and query language
for OBDA, where aggregate and other analytical functions are first class
citizens. Moreover, we develop query optimisation techniques that allow to
efficiently process analytical tasks over static and streaming data. We
implement our approach in a system and evaluate our system with Siemens turbine
data
Ontology-Based Data Access and Integration
An ontology-based data integration (OBDI) system is an information management system consisting of three components: an ontology, a set of data sources, and the mapping between the two. The ontology is a conceptual, formal description of the domain of interest to a given organization (or a community of users), expressed in terms of relevant concepts, attributes of concepts, relationships between concepts, and logical assertions characterizing the domain knowledge. The data sources are the repositories accessible by the organization where data concerning the domain are stored. In the general case, such repositories are numerous, heterogeneous, each one managed and maintained independently from the others. The mapping is a precise specification of the correspondence between the data contained in the data sources and the elements of the ontology. The main purpose of an OBDI system is to allow information consumers to query the data using the elements in the ontology as predicates.
In the special case where the organization manages a single data source, the term ontology-based data access (ODBA) system is used
Metamorphic Domain-Specific Languages: A Journey Into the Shapes of a Language
External or internal domain-specific languages (DSLs) or (fluent) APIs?
Whoever you are -- a developer or a user of a DSL -- you usually have to choose
your side; you should not! What about metamorphic DSLs that change their shape
according to your needs? We report on our 4-years journey of providing the
"right" support (in the domain of feature modeling), leading us to develop an
external DSL, different shapes of an internal API, and maintain all these
languages. A key insight is that there is no one-size-fits-all solution or no
clear superiority of a solution compared to another. On the contrary, we found
that it does make sense to continue the maintenance of an external and internal
DSL. The vision that we foresee for the future of software languages is their
ability to be self-adaptable to the most appropriate shape (including the
corresponding integrated development environment) according to a particular
usage or task. We call metamorphic DSL such a language, able to change from one
shape to another shape
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