Semantic model-driven development of web service architectures.

Building service-based architectures has become a major area of interest since the advent of Web services. Modelling these architectures is a central activity. Model-driven development is a recent approach to developing software systems based on the idea of making models the central artefacts for design representation, analysis, and code generation. We propose an ontology-based engineering methodology for semantic model-driven composition and transformation of Web service architectures. Ontology technology as a logic-based knowledge representation and reasoning framework can provide answers to the needs of sharable and reusable semantic models and descriptions needed for service engineering. Based on modelling, composition and code generation techniques for service architectures, our approach provides a methodological framework for ontology-based semantic service architecture

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

Semantic model-driven development of service-centric software architectures

Service-oriented architecture (SOA) is a recent architectural paradigm that has received much attention. The prevalent focus on platforms such as Web services, however, needs to be complemented by appropriate software engineering methods. We propose the model-driven development of service-centric software systems. We present in particular an investigation into the role of enriched semantic modelling for a modeldriven development framework for service-centric software systems. Ontologies as the foundations of semantic modelling and its enhancement through architectural pattern modelling are at the core of the proposed approach. We introduce foundations and discuss the benefits and also the challenges in this context

DSL-based Interoperability and Integration in the Smart Manufacturing Digital Thread

In the industry 4.0 ecosystem, a Digital Thread connects the data and processes for smarter manufacturing. It provides an end to end integration of the various digital entities thus fostering interoperability, with the aim to design and deliver complex and heterogeneous interconnected systems. We develop a service oriented domain specific Digital Thread platform in a Smart Manufacturing research and prototyping context. We address the principles, architecture and individual aspects of a growing Digital Thread platform. It conforms to the best practices of coordination languages, integration and interoperability of external services from various platforms, and provides orchestration in a formal methods based, low-code and graphical model driven fashion. We chose the Cinco products DIME and Pyrus as the underlying IT platforms for our Digital Thread solution to serve the needs of the applications addressed: manufacturing analytics and predictive maintenance are in fact core capabilities for the success of smart manufacturing operations. In this regard, we extend the capabilities of these two platforms in the vertical domains of data persistence, IoT connectivity and analytics, to support the basic operations of smart manufacturing. External native DSLs provide the data and capability integrations through families of SIBs. The small examples constitute blueprints for the methodology, addressing the knowledge, terminology and concerns of domain stakeholders. Over time, we expect reuse to increase, reducing the new integration and development effort to a progressively smaller portion of the models and code needed for at least the most standard application

A new MDA-SOA based framework for intercloud interoperability

Cloud computing has been one of the most important topics in Information Technology which aims to assure scalable and reliable on-demand services over the Internet. The expansion of the application scope of cloud services would require cooperation between clouds from different providers that have heterogeneous functionalities. This collaboration between different cloud vendors can provide better Quality of Services (QoS) at the lower price. However, current cloud systems have been developed without concerns of seamless cloud interconnection, and actually they do not support intercloud interoperability to enable collaboration between cloud service providers. Hence, the PhD work is motivated to address interoperability issue between cloud providers as a challenging research objective. This thesis proposes a new framework which supports inter-cloud interoperability in a heterogeneous computing resource cloud environment with the goal of dispatching the workload to the most effective clouds available at runtime. Analysing different methodologies that have been applied to resolve various problem scenarios related to interoperability lead us to exploit Model Driven Architecture (MDA) and Service Oriented Architecture (SOA) methods as appropriate approaches for our inter-cloud framework. Moreover, since distributing the operations in a cloud-based environment is a nondeterministic polynomial time (NP-complete) problem, a Genetic Algorithm (GA) based job scheduler proposed as a part of interoperability framework, offering workload migration with the best performance at the least cost. A new Agent Based Simulation (ABS) approach is proposed to model the inter-cloud environment with three types of agents: Cloud Subscriber agent, Cloud Provider agent, and Job agent. The ABS model is proposed to evaluate the proposed framework.Fundação para a Ciência e a Tecnologia (FCT) - (Referencia da bolsa: SFRH SFRH / BD / 33965 / 2009) and EC 7th Framework Programme under grant agreement n° FITMAN 604674 (http://www.fitman-fi.eu

A Multi-Criteria Framework to Assist on the Design of Internet-of-Things Systems

The Internet-of-Things (IoT), considered as Internet first real evolution, has become immensely important to society due to revolutionary business models with the potential to radically improve Human life. Manufacturers are engaged in developing embedded systems (IoT Systems) for different purposes to address this new variety of application domains and services. With the capability to agilely respond to a very dynamic market offer of IoT Systems, the design phase of IoT ecosystems can be enhanced. However, select the more suitable IoT System for a certain task is currently based on stakeholder’s knowledge, normally from lived experience or intuition, although it does not mean that a proper decision is being made. Furthermore, the lack of methods to formally describe IoT Systems characteristics, capable of being automatically used by methods is also an issue, reinforced by the growth of available information directly connected to Internet spread. Contributing to improve IoT Ecosystems design phase, this PhD work proposes a framework capable of fully characterise an IoT System and assist stakeholder’s on the decision of which is the proper IoT System for a specific task. This enables decision-makers to perform a better reasoning and more aware analysis of diverse and very often contradicting criteria. It is also intended to provide methods to integrate energy consumptionsimulation tools and address interoperability with standards, methods or systems within the IoT scope. This is addressed using a model-driven based framework supporting a high openness level to use different software languages and decision methods, but also for interoperability with other systems, tools and methods