Browsing by Keyword "Services"
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Item The Arrowhead Approach for SOA Application Development and Documentation(IEEE, 2015-02-26) Blomstedt, Fredrik; Ferreira, Luis Lino; Klisics, Markus; Chrysoulas, Christos; Martínez de Soria, Iker; Morin, Brice; Zabasta, Anatolijs; Eliasson, Jens; Johansson, Mats; Varga, Pal; Tecnalia Research & InnovationThe Arrowhead project aims to address the technical and applicative issues associated with cooperative automation based on Service Oriented Architectures. The problems of developing such kind of systems are mainly due to the lack of adequate development and service documentation methodologies, which would ease the burden of reusing services on different applications. The Arrowhead project proposes a technical framework to efficiently support the development of such systems, which includes several tools for documentation of services and to support the development of SOA-based installations. The work presented in this paper describes the approach which has been developed for the first generation pilots to support the documentation of their structural services. Each service, system and system-of-systems within the Arrowhead Framework must be documented and described in such way that it can be implemented, tested and deployed in an interoperable way. This paper presents the first steps of realizing the Arrowhead vision for interoperable services, systems and systems-of-systems.Item Making system of systems interoperable – The core components of the arrowhead framework(2016-11) Varga, Pal; Blomstedt, Fredrik; Ferreira, Luis Lino; Eliasson, Jens; Johansson, Mats; Delsing, Jerker; Martínez de Soria, Iker; Tecnalia Research & InnovationThe objective of the Arrowhead Framework is to efficiently support the development, deployment and operation of interconnected, cooperative systems. It is based on the Service Oriented Architecture philosophy. The building elements of the framework are systems that provide and consume services, and cooperate as systems of systems. Some commonly used systems, such as orchestration, authorization or service registry are considered as core. These can be used by any system of systems that follow the guidelines of the Arrowhead Framework. Within the framework, systems – using different information exchange technologies during collaboration – are helped through various approaches. These include the so-called Interoperability Layer, as well as systems and services for translation. Furthermore, one of the main problems of developing such highly interoperable systems is the lack of understanding between various development groups. Adequate development and service documentation methodologies can help to overcome this issue. The design, development and verification methodology for each service, system and system of systems within the Arrowhead Framework supports that these can be implemented, verified, deployed, and run in an interoperable way. This paper presents an overview of the framework together with its core elements – and provides guidelines for the design and deployment of interoperable, Arrowhead-compliant cooperative systems.Item A statistical recommendation model of mobile services based on contextual evidences(2012-01) Picón, Artzai; Rodríguez-Vaamonde, Sergio; Jaén, Javier; Mocholi, Jose Antonio; García, David; Cadenas, Alejandro; COMPUTER_VISION; Tecnalia Research & InnovationMobile devices are undergoing great advances in recent years allowing users to access an increasing number of services or personalized applications that can help them select the best restaurant, locate certain shops, choose the best way home or rent the best film. However this great quantity of services does not require the user to find and select those services needed for each specific situation. The classical approaches link some preferences to certain services, include the recommendations given by other users or even include certain fixed rules in order to choose the most appropriate services. However, since these methods assume that user needs can be modelled by fixed rules or preferences, they fail when modelling different users or makes them difficult to train. In this paper we propose a new algorithm that learns from the user's actions in different contextual situations, which allows to properly infer the most appropriate recommendations for a user in a specific contextual situation. This model, by using of a double knowledge diffusion approach, has been specifically designed to face the inherent lack of learning evidences, computational cost and continuous training requirements and, therefore, overcomes the performance and convergence rates offered by other learning methodologies.