A MDD Strategy for developing Context-Aware Pervasive Systems

This master thesis proposes a methodological approach to develop context-aware pervasive systems based on ontologies and the Model-Driven Development (MDD) guidelines.Serral Asensio, E. (2008). A MDD Strategy for developing Context-Aware Pervasive Systems. http://hdl.handle.net/10251/12446Archivo delegad

Context-Adaptive Coordination of Pervasive Services by Interpreting Models during Runtime

[EN] One of the most important goals of pervasive systems is to help users in their daily life by automating their behaviour patterns. To achieve this, pervasive services must be dynamically coordinated, executed and adapted to context according to user behaviour patterns. In this work, we propose a model-driven solution to meet this challenge. We propose a task model and a context ontology to design context-adaptive coordination of services at a high level of abstraction. This design facilitates the coordination analysis at design time and is also reused at runtime. We propose a software architecture that interprets the models at runtime in order to coordinate the service execution that is required to support user behaviour patterns. This coordination is done in a context-adaptive way and decoupled from service implementation. This approach makes the models the only representation of service coordination, which facilitates the maintenance and evolution of the executed service coordination after deployment.This work has been developed with the support of (a) MICINN under the project EVERYWARE TIN2010-18011 and (b) MITYC under the project LIFEWEAR TSI-020400-2010-100 co-funded with ERDF.Serral Asensio, E.; Valderas Aranda, PJ.; Pelechano Ferragud, V. (2013). Context-Adaptive Coordination of Pervasive Services by Interpreting Models during Runtime. Computer Journal. 56(1):87-114. https://doi.org/10.1093/comjnl/bxs019S8711456

Hearing the voice of citizens in smart city design:The CitiVoice framework

In the last few years, smart cities have attracted considerable attention because they are considered a response to the complex challenges that modern cities face. However, smart cities often do not optimally reach their objectives if the citizens, the end-users, are not involved in their design. The aim of this paper is to provide a framework to structure and evaluate citizen participation in smart cities. By means of a literature review from different research areas, the relevant enablers of citizen participation are summarized and bundled in the proposed CitiVoice framework. Then, following the design science methodology, the content and the utility of CitiVoice are validated through the application to different smart cities and through in-depth interviews with key Belgian smart city stakeholders. CitiVoice is used as an evaluation tool for several Belgian smart cities allowing drawbacks and flaws in citizens’ participation to be discovered and analysed. It is also demonstrated how CitiVoice can act as a governance tool for the ongoing smart city design of Namur (Belgium) to help define the citizen participation strategy. Finally, it is used as a comparison and creativity tool to compare several cities and design new means of participation.status: publishe

Decision as a Service (DaaS):A service-oriented architecture approach for decisions in processes

Separating decision modelling from the processes modelling concern recently gained significant support in literature, as incorporating both concerns into a single model impairs the scalability, maintainability, flexibility and understandability of both processes and decisions. Most notably the introduction of the Decision Model and Notation (DMN) standard by the Object Management Group provides a suitable solution for externalising decisions from processes and automating decision enactments for processes. This paper introduces a systematic way of tackling the separation of the decision modelling concern from process modelling by providing a Decision as a Service (DaaS) layered Service-Oriented Architecture (SOA) which approaches decisions as automated and externalised services that processes need to invoke on demand to obtain the decision outcome. The DaaS mechanism is elucidated by a formalisation of DMN constructs and the relevant layer elements. Furthermore, DaaS is evaluated against the fundamental characteristics of the SOA paradigm, proving its contribution in terms of abstraction, reusability, loose coupling, and other pertinent SOA principles. Additionally, the benefits of the DaaS design on process-decision modelling and mining are discussed. Finally, the DaaS design is illustrated on a real-life event log of a bank loan application and approval process, and the SOA maturity of DaaS is assessed.status: Published onlin

Supporting ambient assisting living by using executable context-adaptive task models

[EN] The amount of elderly people with chronic diseases is constantly increasing, and current health systems are not able to provide a proper supervision. Ambient Assisted Living (AAL) is a new research area that stands for the use of pervasive and mobile technologies in order to increase the quality of life, wellbeing and safety of elderly people. In this work, we present a tool-supported methodology to facilitate the creation of AAL systems through the use of executable models. AAL services are specified by executable context-adaptive task models by using concepts of a high level of abstraction, which facilitate the participation of medical professionals in the AAL specification. The task models are then interpreted and executed at runtime by a software infrastructure that automates the AAL services as specified. Thus, task models are the only implementation of the services, making it easy their further evolution after system deployment. In order to demonstrate the feasibility of our methodology, we have evaluated it in the development of an AAL system for assisting the patients of a nursing home.Serral Asensio, E.; Valderas Aranda, PJ.; Pelechano Ferragud, V. (2014). Supporting ambient assisting living by using executable context-adaptive task models. International Journal On Advances in Software. 7(1&2):77-87. http://hdl.handle.net/10251/52206S778771&

A Software Infrastructure for Executing Adaptive Daily Routines in Smart Automation Environments

[EN] Since the advent of Pervasive Computing, the execution of user daily routines in an adaptive way has been a widely pursued challenge. Its achievement would not only reduce the tasks that users must perform every day, but it would also perform them in a more convenient way while optimizing natural resource consumption. In this work, we meet this challenge by providing a software infrastructure. It allows users’ routines to be automated in a non-intrusive way by taking into account users’ automation desires and demands. We demonstrate this by performing a case-study based evaluation.This work has been supported by the Christian Doppler Forschungsgesellschaft and the BMWFJ, Austria.Serral Asensio, E.; Valderas Aranda, PJ.; Pelechano Ferragud, V. (2013). A Software Infrastructure for Executing Adaptive Daily Routines in Smart Automation Environments. IARIA XPS Press (International Academy, Research, and Industry Association). http://hdl.handle.net/10251/75236

Reviewing technical approaches for sharing and preservation of experimental data

Empirical Software Engineering (ESE) replication researchers need to store and manipulate experimental data for several purposes, in particular analysis and reporting. Current research needs call for sharing and preservation of experimental data as well. In a previous work, we analyzed Replication Data Management (RDM) needs. A novel concept, called Experimental Ecosystem, was proposed to solve current deficiencies in RDMapproaches. The empirical ecosystem provides replication researchers with a common framework that integrates transparently local heterogeneous data sources. A typical situation where the Empirical Ecosystem is applicable, is when several members of a research group, or several research groups collaborating together, need to share and access each other experimental results. However, to be able to apply the Empirical Ecosystem concept and deliver all promised benefits, it is necessary to analyze the software architectures and tools that can properly support it

Replication Data Management,needs and solutions: an initial evaluation of conceptual approaches for integrating heterogeneous replication study data

Replication Data Management (RDM) aims at enabling the use of data collections from several iterations of an experiment. However, there are several major challenges to RDM from integrating data models and data from empirical study infrastructures that were not designed to cooperate, e.g., data model variation of local data sources. [Objective] In this paper we analyze RDM needs and evaluate conceptual RDM approaches to support replication researchers. [Method] We adapted the ATAM evaluation process to (a) analyze RDM use cases and needs of empirical replication study research groups and (b) compare three conceptual approaches to address these RDM needs: central data repositories with a fixed data model, heterogeneous local repositories, and an empirical ecosystem. [Results] While the central and local approaches have major issues that are hard to resolve in practice, the empirical ecosystem allows bridging current gaps in RDM from heterogeneous data sources. [Conclusions] The empirical ecosystem approach should be explored in diverse empirical environments