Proactive services ecosystem framework

Dissertation presented to obtain the degree of Doctor in Electrical and Computer Engineering, specialization on Collaborative Enterprise NetworksCollaborative-Networks (CN) have experienced a fast evolution in the last two decades. The collaboration among independent entities or professionals supported by Information and Communication Technology (ICT) has attracted the research community to establish the conceptual basis for this scientific discipline. Service Orientation has been one of the key selected paradigms for that conceptual basis. Nevertheless, the service concept itself does not have a common understanding in the Business and ICT worlds. In the former, client satisfaction, resources management and business process models are some example concerns, whilst the later deals with interoperability, remote function calling or communication protocols. If for example an enterprise provides some service, it may hire specialists to wrap such service into web-services, expecting to reach worldwide potential new clients. In fact, nowadays Web Services and Service Oriented Architectures (SOA) are the technological elements most commonly used. However, these are passive elements in the sense they do not perform any action towards pursuing business interests, which constitute a limiting factor from a business perspective. Another approach for the above mentioned enterprise is to follow the Multi-Agent Systems (MAS) approach, as the pro-activity is a keyword in such contexts. Nevertheless, as MAS approaches are not so commonly used and not so robust yet, the worldwide potential set of new clients is reduced; which also constitutes an inhibitor factor from the business perspective. This dissertation proposes a Pro-Active Services Ecosystem Framework, gathering inspiration from both the SOA and MAS research areas, trying to bridge the business and ICT worlds through the base concepts for the creation of a Services’ Ecosystem where business services are represented in a pro-active manner towards pursuing business interests, like finding collaboration opportunities or improving the chances each CN member has to see its services selected among competitors, for example. This work also includes a prototype system applied / validated in the area of a Professional Virtual Community of Senior Professionals

Big data reference architecture for industry 4.0: including economic and ethical Implications

El rápido progreso de la Industria 4.0 se consigue gracias a las innovaciones en varios campos, por ejemplo, la fabricación, el big data y la inteligencia artificial. La tesis explica la necesidad de una arquitectura del Big Data para implementar la Inteligencia Artificial en la Industria 4.0 y presenta una arquitectura cognitiva para la inteligencia artificial - CAAI - como posible solución, que se adapta especialmente a los retos de las pequeñas y medianas empresas. La tesis examina las implicaciones económicas y éticas de esas tecnologías y destaca tanto los beneficios como los retos para los países, las empresas y los trabajadores individuales. El "Cuestionario de la Industria 4.0 para las PYME" se realizó para averiguar los requisitos y necesidades de las pequeñas y medianas empresas. Así, la nueva arquitectura de la CAAI presenta un modelo de diseño de software y proporciona un conjunto de bloques de construcción de código abierto para apoyar a las empresas durante la implementación. Diferentes casos de uso demuestran la aplicabilidad de la arquitectura y la siguiente evaluación verifica la funcionalidad de la misma.The rapid progress in Industry 4.0 is achieved through innovations in several fields, e.g., manufacturing, big data, and artificial intelligence. The thesis motivates the need for a Big Data architecture to apply artificial intelligence in Industry 4.0 and presents a cognitive architecture for artificial intelligence – CAAI – as a possible solution, which is especially suited for the challenges of small and medium-sized enterprises. The work examines the economic and ethical implications of those technologies and highlights the benefits but also the challenges for countries, companies and individual workers. The "Industry 4.0 Questionnaire for SMEs" was conducted to gain insights into smaller and medium-sized companies’ requirements and needs. Thus, the new CAAI architecture presents a software design blueprint and provides a set of open-source building blocks to support companies during implementation. Different use cases demonstrate the applicability of the architecture and the following evaluation verifies the functionality of the architecture