Yolande Berbers

Towards an Extensible Context Ontology for Ambient Intelligence

To realise an Ambient Intelligence environment, it is paramount that applications can dispose of information about the context in which they operate, preferably in a very general manner. For this purpose various types of information should be assembled to form a representation of the context of the device on which aforementioned applications run. To allow interoperability in an Ambient Intelligence environment, it is necessary that the context terminology is commonly understood by all participating devices. In this paper we propose an adaptable and extensible context ontology for creating context-aware computing infrastructures, ranging from small embedded devices to high-end service platforms. The ontology has been designed to solve several key challenges in Ambient Intelligence, such as application adaptation, automatic code generation and code mobility, and generation of device specific user interfaces.

EASY: Efficient semAntic Service discoverY in pervasive computing environments with QoS and context support

Pervasive computing environments are populated with networked software and hardware resources providing various functionalities that are abstracted, thanks to the Service Oriented Architecture paradigm, as services. Within these environments, service discovery enabled by service discovery protocols (SDPs) is a critical functionality for establishing ad hoc associations between service providers and service requesters. Furthermore, the dynamics, the openness and the user-centric vision aimed at by the pervasive computing paradigm call for solutions that enable rich, semantic, context- and QoS-aware service discovery. Although the semantic Web paradigm envisions to achieve such support, current solutions are hardly deployable in the pervasive environment due to the costly underlying semantic reasoning with ontologies. In this article, we present EASY to support efficient, semantic, context- and QoS-aware service discovery on top of existing SDPs. EASY provides EASY-L, a language for semantic specification of functional and non-functional service properties, as well as EASY-M, a corresponding set of conformance relations. Furthermore, EASY provides solutions to efficiently assess conformance between service capabilities. These solutions are based on an efficient encoding technique, as well as on an efficient organization of service repositories (caches), which enables both fast service advertising and discovery. Experimental results show that the deployment of EASY on top of an existing SDP, namely Ariadne, enhancing it only with slight changes to EASY-Ariadne, enables rich semantic, context- and QoS-aware service discovery, which furthermore performs better than the classical, rigid, syntactic matching, and improves the scalability of Ariadne.

Tranquility: A Low Disruptive Alternative to Quiescence for Ensuring Safe Dynamic Updates

This paper revisits a problem that was identified by Kramer and Magee: placing a system in a consistent state before and after runtime changes. We show that their notion of quiescence as a necessary and sufficient condition for safe runtime changes is too strict and results in a significant disruption in the application being updated. In this paper, we introduce a weaker condition: tranquillity. We show that tranquillity is easier to obtain and less disruptive for the running application but still a sufficient condition to ensure application consistency. We present an implementation of our approach on a component middleware platform and experimentally verify the validity and practical applicability of our approach using data retrieved from a case study.

Mobile phones assisting with health self-care: a diabetes case study

The applicability of pervasive and mobile computing in the health care sector is beyond dispute. This paper explores the use of the mobile phone as a tool for personalized health care assistance for individuals diagnosed with diabetes. By monitoring user location and activity on the mobile phone, recognizing past behavior and augmenting the logging of blood glucose levels with context data, our prototype application assists with taking well-informed decisions on daily drug dosage to achieve and maintain stable blood glucose levels. Evaluation of the prototype application indicate that a brief training of the application suffices to capture patterns in the users relevant context that simplify glucose level trends analysis. We describe some of the details of the user study and the prototype application, and conclude with plans to investigate context-driven activity prediction to further improve the decision support for the user.

UniTI: a unified transformation infrastructure

A model transformation can be decomposed into a sequence of subtransformations, i.e. a transformation chain, each addressing a limited set of concerns. However, with current transformation technologies it is hard to (re)use and compose subtransformations without being very familiar with their implementation details. Furthermore, the difficulty of combining different transformation technologies often thwarts choosing the most appropriate technology for each subtransformation. In this paper we propose a model-based approach to reuse and compose subtransformations in a technology-independent fashion. This is accomplished by developing a unified representation of transformations and facilitating detailed transformation specifications. We have implemented our approach in a tool called UniTI, which also provides a transformation chain editor. We have evaluated our approach by comparing it to alternative approaches.

Constructing and Visualizing Transformation Chains

Model transformations can be defined by a chain or network of sub-transformations, each fulfilling a specific task. Many intermediate models, possibly accompanied by traceability models, are thus generated before reaching the final target(s). There is a need for tools that assist the developer in managing and interpreting this growing amount of MDD artifacts. In this paper we first discuss how a transformation chain can be modeled and executed in a transformation language independent way. We then explore how the available traceability information can be used to generate suitable diagrams for all intermediate and final models. We also propose a technique to visualize all the diagrams along with their traceability information in a single view by using a 3D diagram editor. Finally, we present an example transformation chain that has been modeled, executed and visualized using our tools.

Power-reduction techniques for data-center storage systems

As data-intensive, network-based applications proliferate, the power consumed by the data-center storage subsystem surges. This survey summarizes, organizes, and integrates a decade of research on power-aware enterprise storage systems. All of the existing power-reduction techniques are classified according to the disk-power factor and storage-stack layer addressed. A majority of power-reduction techniques is based on dynamic power management. We also consider alternative methods that reduce disk access time, conserve space, or exploit energy-efficient storage hardware. For every energy-conservation technique, the fundamental trade-offs between power, capacity, performance, and dependability are uncovered. With this survey, we intend to stimulate integration of different power-reduction techniques in new energy-efficient file and storage systems.

MDD approach for the development of context-aware applications

Context-aware systems offer entirely new opportunities for application developers and for end users by gathering context information and adapting systems behavior accordingly. Several context models have been defined and various context-aware middleware has been developed in order to simplify the development of context-aware applications. Unfortunately, the development of an application by using these middleware products introduces several technical details in the application. These technical details are specific to a given middleware and reduce the possibility of reusing the application on other middleware. In this paper, we propose an MDD (Model Driven Development) approach that makes it possible to design context-aware applications independently of the platform. This approach is based on several phases that approach step by step the context platform and allow designers to automatically map their models to several platforms through the definition of automatic and modular transformations. To be able to apply this approach we define a new UML profile for context-aware applications, that we use to explore our approach.

Genetic algorithm-based optimization of service composition and deployment

Services running on mobile systems must be able to adapt themselves to changing user needs and availability of resources. We propose to use Genetic Algorithms to search for the best service variant in the current context. The chosen service composition is then deployed on a set of available nodes in an optimal way. We illustrate that Genetic Algorithms provide a scalable and self-organizing solution to service composition and deployment. We argue that the approach meets some main requirements demanded by services running on mobile systems. A motivating scenario is presented in which a distributed server allows users to share content and run applications in mobile ad-hoc networks.

Inter-DSL coordination support by combining megamodeling and model weaving

Model-Driven Engineering (MDE) advocates the use of models at every step of the software development process. Within this context, a team of engineers collectively and collaboratively contribute to a large set of interrelated models. Even if the main focus can be on a single model (e.g. a class diagram model), related elements in other models (e.g. a requirement model) often have to be considered and/or accessed. Moreover, all the involved models do not necessarily conform to the same metamodel and thus may have been built using different independent Domain-Specific Languages (DSLs). Such a situation has already been frequently observed in many large-scale industrial deployments of MDE. Manually coordinating all the involved models, i.e. being able to both manage and use the links existing between them, can become a cumbersome and difficult task. As a proposal to solve this inter-DSL coordination issue, we introduce in this paper a generic and extensible inter-model traceability and navigation environment based on the complementary use of megamodeling and model weaving. We illustrate our solution with a concrete working example.