7,425 research outputs found
Towards More Data-Aware Application Integration (extended version)
Although most business application data is stored in relational databases,
programming languages and wire formats in integration middleware systems are
not table-centric. Due to costly format conversions, data-shipments and faster
computation, the trend is to "push-down" the integration operations closer to
the storage representation.
We address the alternative case of defining declarative, table-centric
integration semantics within standard integration systems. For that, we replace
the current operator implementations for the well-known Enterprise Integration
Patterns by equivalent "in-memory" table processing, and show a practical
realization in a conventional integration system for a non-reliable,
"data-intensive" messaging example. The results of the runtime analysis show
that table-centric processing is promising already in standard, "single-record"
message routing and transformations, and can potentially excel the message
throughput for "multi-record" table messages.Comment: 18 Pages, extended version of the contribution to British
International Conference on Databases (BICOD), 2015, Edinburgh, Scotlan
Enabling stream processing for people-centric IoT based on the fog computing paradigm
The world of machine-to-machine (M2M) communication is gradually moving from vertical single purpose solutions to multi-purpose and collaborative applications interacting across industry verticals, organizations and people - A world of Internet of Things (IoT). The dominant approach for delivering IoT applications relies on the development of cloud-based IoT platforms that collect all the data generated by the sensing elements and centrally process the information to create real business value. In this paper, we present a system that follows the Fog Computing paradigm where the sensor resources, as well as the intermediate layers between embedded devices and cloud computing datacenters, participate by providing computational, storage, and control. We discuss the design aspects of our system and present a pilot deployment for the evaluating the performance in a real-world environment. Our findings indicate that Fog Computing can address the ever-increasing amount of data that is inherent in an IoT world by effective communication among all elements of the architecture
A model-driven approach to broaden the detection of software performance antipatterns at runtime
Performance antipatterns document bad design patterns that have negative
influence on system performance. In our previous work we formalized such
antipatterns as logical predicates that predicate on four views: (i) the static
view that captures the software elements (e.g. classes, components) and the
static relationships among them; (ii) the dynamic view that represents the
interaction (e.g. messages) that occurs between the software entities elements
to provide the system functionalities; (iii) the deployment view that describes
the hardware elements (e.g. processing nodes) and the mapping of the software
entities onto the hardware platform; (iv) the performance view that collects
specific performance indices. In this paper we present a lightweight
infrastructure that is able to detect performance antipatterns at runtime
through monitoring. The proposed approach precalculates such predicates and
identifies antipatterns whose static, dynamic and deployment sub-predicates are
validated by the current system configuration and brings at runtime the
verification of performance sub-predicates. The proposed infrastructure
leverages model-driven techniques to generate probes for monitoring the
performance sub-predicates and detecting antipatterns at runtime.Comment: In Proceedings FESCA 2014, arXiv:1404.043
NEOREG : design and implementation of an online neonatal registration system to access, follow and analyse data of newborns with congenital cytomegalovirus infection
Today's registration of newborns with congenital cytomegalovirus (cCMV) infection is still performed on paper-based forms in Flanders, Belgium. This process has a large administrative impact. It is imortant that all screening tests are registered to have a complete idea of the impact of cCMV. Although these registrations are usable in computerised data analysis, these data are not available in a format to perform electronic processing. An online Neonatal Registry (NEOREG) System was designed and developed to access, follow and analyse the data of newborns remotely. It allows patients' diagnostic registration and treatment follow-up through a web interface and uses document forms in Portable Document Format (PDF), which incorporate all the elements from the existing forms. Forms are automatically processed to structured EHRs. Modules are included to perform statistical analysis. The design was driven by extendibility, security and usability requirements. The website load time, throughput and execution time of data analysis were evaluated in detail. The NEOREG system is able to replace the existing paper-based CMV records
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