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

Achieving Autonomic Web Service Compositions with Models at Runtime

Over the last years, Web services have become increasingly popular. It is because they allow businesses to share data and business process (BP) logic through a programmatic interface across networks. In order to reach the full potential of Web services, they can be combined to achieve specifi c functionalities. Web services run in complex contexts where arising events may compromise the quality of the system (e.g. a sudden security attack). As a result, it is desirable to count on mechanisms to adapt Web service compositions (or simply called service compositions) according to problematic events in the context. Since critical systems may require prompt responses, manual adaptations are unfeasible in large and intricate service compositions. Thus, it is suitable to have autonomic mechanisms to guide their self-adaptation. One way to achieve this is by implementing variability constructs at the language level. However, this approach may become tedious, difficult to manage, and error-prone as the number of con figurations for the service composition grows. The goal of this thesis is to provide a model-driven framework to guide autonomic adjustments of context-aware service compositions. This framework spans over design time and runtime to face arising known and unknown context events (i.e., foreseen and unforeseen at design time) in the close and open worlds respectively. At design time, we propose a methodology for creating the models that guide autonomic changes. Since Service-Oriented Architecture (SOA) lacks support for systematic reuse of service operations, we represent service operations as Software Product Line (SPL) features in a variability model. As a result, our approach can support the construction of service composition families in mass production-environments. In order to reach optimum adaptations, the variability model and its possible con figurations are verifi ed at design time using Constraint Programming (CP). At runtime, when problematic events arise in the context, the variability model is leveraged for guiding autonomic changes of the service composition. The activation and deactivation of features in the variability model result in changes in a composition model that abstracts the underlying service composition. Changes in the variability model are refl ected into the service composition by adding or removing fragments of Business Process Execution Language (WS-BPEL) code, which are deployed at runtime. Model-driven strategies guide the safe migration of running service composition instances. Under the closed-world assumption, the possible context events are fully known at design time. These events will eventually trigger the dynamic adaptation of the service composition. Nevertheless, it is diffi cult to foresee all the possible situations arising in uncertain contexts where service compositions run. Therefore, we extend our framework to cover the dynamic evolution of service compositions to deal with unexpected events in the open world. If model adaptations cannot solve uncertainty, the supporting models self-evolve according to abstract tactics that preserve expected requirements.Alférez Salinas, GH. (2013). Achieving Autonomic Web Service Compositions with Models at Runtime [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/34672TESI

A context model for semantic mediation in Web services composition

This paper presents a context-driven approach that aims at supporting semantic mediation between composed Web services. Despite the widespread adoption of Web services by the IT community, innovative solutions are needed in order to overcome the challenging issue that relates to the semantic disparity of exchanged data. Indeed, there is a lack of means for interpreting these data according to the contextual requirements of each Web service. The context-driven approach suggests two steps. The first step consists of developing a model for anchoring context to data flowing between Web services. In the second step, we use this model to support the semantic mediation between Web services engaged in a composition. © Springer-Verlag Berlin Heidelberg 2006

A Platform-independent Programming Environment for Robot Control

The development of robot control programs is a complex task. Many robots are different in their electrical and mechanical structure which is also reflected in the software. Specific robot software environments support the program development, but are mainly text-based and usually applied by experts in the field with profound knowledge of the target robot. This paper presents a graphical programming environment which aims to ease the development of robot control programs. In contrast to existing graphical robot programming environments, our approach focuses on the composition of parallel action sequences. The developed environment allows to schedule independent robot actions on parallel execution lines and provides mechanism to avoid side-effects of parallel actions. The developed environment is platform-independent and based on the model-driven paradigm. The feasibility of our approach is shown by the application of the sequencer to a simulated service robot and a robot for educational purpose

RESTful Service Composition

The Service-Oriented Architecture (SOA) has become one of the most popular approaches to building large-scale network applications. The web service technologies are de facto the default implementation for SOA. Simple Object Access Protocol (SOAP) is the key and fundamental technology of web services. Service composition is a way to deliver complex services based on existing partner services. Service orchestration with the support of Web Services Business Process Execution Language (WSBPEL) is the dominant approach of web service composition. WSBPEL-based service orchestration inherited the issue of interoperability from SOAP, and it was furthermore challenged for performance, scalability, reliability and modifiability. I present an architectural approach for service composition in this thesis to address these challenges. An architectural solution is so generic that it can be applied to a large spectrum of problems. I name the architectural style RESTful Service Composition (RSC), because many of its elements and constraints are derived from Representational State Transfer (REST). REST is an architectural style developed to describe the architectural style of the Web. The Web has demonstrated outstanding interoperability, performance, scalability, reliability and modifiability. RSC is designed for service composition on the Internet. The RSC style is composed on specific element types, including RESTful service composition client, RESTful partner proxy, composite resource, resource client, functional computation and relaying service. A service composition is partitioned into stages; each stage is represented as a computation that has a uniform identifier and a set of uniform access methods; and the transitions between stages are driven by computational batons. RSC is supplemented by a programming model that emphasizes on-demand function, map-reduce and continuation passing. An RSC-style composition does not depend on either a central conductor service or a common choreography specification, which makes it different from service orchestration or service choreography. Four scenarios are used to evaluate the performance, scalability, reliability and modifiability improvement of the RSC approach compared to orchestration. An RSC-style solution and an orchestration solution are compared side by side in every scenario. The first scenario evaluates the performance improvement of the X-Ray Diffraction (XRD) application in ScienceStudio; the second scenario evaluates the scalability improvement of the Process Variable (PV) snapshot application; the third scenario evaluates the reliability improvement of a notification application by simulation; and the fourth scenario evaluates the modifiability improvement of the XRD application in order to fulfil emerging requirements. The results show that the RSC approach outperforms the orchestration approach in every aspect

Requirements-driven self-optimization of composite services using feedback control

In an uncertain and changing environment, a composite service needs to continuously optimize its business process and service selection through runtime adaptation. To achieve the overall satisfaction of stakeholder requirements, quality tradeoffs are needed to adapt the composite service in response to the changing environments. Existing approaches on service selection and composition, however, are mostly based on quality preferences and business processes decisions made statically at the design time. In this paper, we propose a requirements-driven self-optimization approach for composite services. It measures the quality of services (QoS), estimates the earned business value, and tunes the preference ranks through a feedback loop. The detection of unexpected earned business value triggers the proposed self-optimization process systematically. At the process level, a preference-based reasoner configures a requirements goal model according to the tuned preference ranks of QoS requirements, reconfiguring the business process according to its mappings from the goal configurations. At the service level, selection decisions are optimized by utilizing the tuned weights of QoS criteria. We used an experimental study to evaluate the proposed approach. Results indicate that the new approach outperforms both fixed-weighted and floating-weighted service selection approaches with respect to earned business value and adaptation flexibility

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