22,868 research outputs found
Quality-aware model-driven service engineering
Service engineering and service-oriented architecture as an integration and platform technology is a recent approach to software systems integration. Quality aspects
ranging from interoperability to maintainability to performance are of central importance for the integration of heterogeneous, distributed service-based systems. Architecture models can substantially influence quality attributes of the implemented software systems. Besides the benefits of explicit architectures on maintainability and reuse, architectural constraints such as styles, reference architectures and architectural patterns can influence observable software properties such as performance. Empirical performance evaluation is a process of measuring and evaluating the performance of implemented software. We present an approach for addressing the quality of services and service-based systems at the model-level in the context of model-driven service engineering. The focus on architecture-level models is a consequence of the black-box
character of services
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Middleware architectures for the smart grid: A survey on the state-of-the-art, taxonomy and main open issues
The integration of small-scale renewable energy sources in the smart grid depends on several challenges that must be overcome. One of them is the presence of devices with very different characteristics present in the grid or how they can interact among them in terms of interoperability and data sharing. While this issue is usually solved by implementing a middleware layer among the available pieces of equipment in order to hide any hardware heterogeneity and offer the application layer a collection of homogenous resources to access lower levels, the variety and differences among them make the definition of what is needed in each particular case challenging. This paper offers a description of the most prominent middleware architectures for the smart grid and assesses the functionalities they have, considering the performance and features expected from them in the context of this application domain
The future of technology enhanced active learning â a roadmap
The notion of active learning refers to the active involvement of learner in the learning process,
capturing ideas of learning-by-doing and the fact that active participation and knowledge construction leads to deeper and more sustained learning. Interactivity, in particular learnercontent interaction, is a central aspect of technology-enhanced active learning. In this roadmap,
the pedagogical background is discussed, the essential dimensions of technology-enhanced active learning systems are outlined and the factors that are expected to influence these systems currently and in the future are identified. A central aim is to address this promising field from a
best practices perspective, clarifying central issues and formulating an agenda for future developments in the form of a roadmap
Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions
Traditional power grids are being transformed into Smart Grids (SGs) to
address the issues in existing power system due to uni-directional information
flow, energy wastage, growing energy demand, reliability and security. SGs
offer bi-directional energy flow between service providers and consumers,
involving power generation, transmission, distribution and utilization systems.
SGs employ various devices for the monitoring, analysis and control of the
grid, deployed at power plants, distribution centers and in consumers' premises
in a very large number. Hence, an SG requires connectivity, automation and the
tracking of such devices. This is achieved with the help of Internet of Things
(IoT). IoT helps SG systems to support various network functions throughout the
generation, transmission, distribution and consumption of energy by
incorporating IoT devices (such as sensors, actuators and smart meters), as
well as by providing the connectivity, automation and tracking for such
devices. In this paper, we provide a comprehensive survey on IoT-aided SG
systems, which includes the existing architectures, applications and prototypes
of IoT-aided SG systems. This survey also highlights the open issues,
challenges and future research directions for IoT-aided SG systems
Interoperability of Information Systems and Heterogenous Databases Using XML
Interoperabilily of information systerrrs is the most critical issue facing businesse!
that need to access information from multiple idormution systems on
tlifferent environments ancl diverse platforms. Interoperability has been a basic
requirement for the modern information systems in a competitive and volatile
business environment, particularly with the advent of distributed network system
and the growing relevance of inter-network communications. Our objective
in tltis paper is to develop a comprehensiveframework tofacilitate interoperability
smong distributed and heterogeneous information systems and to develop prototype
software to validate tlte application of XML in interoperability of infurmation
systems and databases
ClouNS - A Cloud-native Application Reference Model for Enterprise Architects
The capability to operate cloud-native applications can generate enormous
business growth and value. But enterprise architects should be aware that
cloud-native applications are vulnerable to vendor lock-in. We investigated
cloud-native application design principles, public cloud service providers, and
industrial cloud standards. All results indicate that most cloud service
categories seem to foster vendor lock-in situations which might be especially
problematic for enterprise architectures. This might sound disillusioning at
first. However, we present a reference model for cloud-native applications that
relies only on a small subset of well standardized IaaS services. The reference
model can be used for codifying cloud technologies. It can guide technology
identification, classification, adoption, research and development processes
for cloud-native application and for vendor lock-in aware enterprise
architecture engineering methodologies
Towards a Model-driven Performance Prediction Approach for Internet of Things Architectures
Indisputable, security and interoperability play major concerns in Internet of Things (IoT) architectures and applications. In this paper, however, we emphasize the role and importance of performance and scalability as additional, crucial aspects in planning and building sustainable IoT solutions. IoT architectures are complicated system-of-systems that include different developer roles, development processes, organizational units, and a multilateral governance. Its performance is often neglected during development but becomes a major concern at the end of development and results in supplemental efforts, costs, and refactoring. It should not be relied on linearly scaling for such systems only by using up-to-date technologies that may promote such behavior. Furthermore, different security or interoperability choices also have a considerable impact on performance and may result in unforeseen trade-offs. Therefore, we propose and pursue the vision of a model-driven approach to predict and evaluate the performance of IoT architectures early in the system lifecylce in order to guarantee efficient and scalable systems reaching from sensors to business applications
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