1,546 research outputs found
Achieving autonomic Web service compositions with models at runtime
[EN] Several exceptional situations may arise in the complex, heterogeneous, and changing contexts
where Web service operations run. For instance, a Web service operation may have
greatly increased its execution time or may have become unavailable. The contribution
of this article is to provide a tool-supported framework to guide autonomic adjustments
of context-aware service compositions using models at runtime. During execution, when
problematic events arise in the context, models are used by an autonomic architecture to
guide changes of the service composition. Under the closed-world assumption, the possible
context events are fully known at design time. Nevertheless, it is difficult to foresee
all the possible situations arising in uncertain contexts where service compositions run.
Therefore, the proposed framework also covers the dynamic evolution of service compositions
to deal with unexpected events in the open world. An evaluation demonstrates that
our framework is efficient during dynamic adjustments.Alférez-Salinas, GH.; Pelechano Ferragud, V. (2017). Achieving autonomic Web service compositions with models at runtime. Computers & Electrical Engineering. 63:332-352. doi:10.1016/j.compeleceng.2017.08.004S3323526
Microservice Transition and its Granularity Problem: A Systematic Mapping Study
Microservices have gained wide recognition and acceptance in software
industries as an emerging architectural style for autonomic, scalable, and more
reliable computing. The transition to microservices has been highly motivated
by the need for better alignment of technical design decisions with improving
value potentials of architectures. Despite microservices' popularity, research
still lacks disciplined understanding of transition and consensus on the
principles and activities underlying "micro-ing" architectures. In this paper,
we report on a systematic mapping study that consolidates various views,
approaches and activities that commonly assist in the transition to
microservices. The study aims to provide a better understanding of the
transition; it also contributes a working definition of the transition and
technical activities underlying it. We term the transition and technical
activities leading to microservice architectures as microservitization. We then
shed light on a fundamental problem of microservitization: microservice
granularity and reasoning about its adaptation as first-class entities. This
study reviews state-of-the-art and -practice related to reasoning about
microservice granularity; it reviews modelling approaches, aspects considered,
guidelines and processes used to reason about microservice granularity. This
study identifies opportunities for future research and development related to
reasoning about microservice granularity.Comment: 36 pages including references, 6 figures, and 3 table
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
Temporal meta-model framework for Enterprise Information Systems (EIS) development
This thesis has developed a Temporal Meta-Model Framework for semi-automated Enterprise System Development, which can help drastically reduce the time and cost to develop, deploy and maintain Enterprise Information Systems throughout their lifecycle. It proposes that the analysis and requirements gathering can also perform the bulk of the design phase, stored and available in a suitable model which would then be capable of automated execution with the availability of a set of specific runtime components
Applying Software Product Lines to Build Autonomic Pervasive Systems
In this Master Thesis, we have proposed a model-driven Software Product Line (SPL) for developing autonomic pervasive systems. The work focusses on reusing the Variability knowledge from the SPL design to the SPL products. This Variability knowledge enables SPL products to deal with adaptation scenarios (evolution and involution) in an autonomic way.Cetina Englada, C. (2008). Applying Software Product Lines to Build Autonomic Pervasive Systems. http://hdl.handle.net/10251/12447Archivo delegad
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