VOLARE: Adaptive Web Service Discovery Middleware for Mobile Systems

With the recent advent and widespread use of smart mobile devices, the flexibility and versatility offered by Service Oriented Architecture's (SOA) makes it an ideal approach to use in the rapidly changing mobile environment. However, the mobile setting presents a set of new challenges that service discovery methods developed for nonmobile environments cannot address. The requirements a mobile client device will have from a Web service may change due to changes in the context or the resources of the client device. In a similar manner, a mobile device that acts as a Web service provider will have different capabilities depending on its status, which may also change dramatically during runtime. This paper introduces VOLARE, a middleware-based solution that will monitor the resources and context of the device, and adapt service requests accordingly. The same method will be used to adapt the Quality of Service (QoS) levels advertised by service providers, to realistically reflect each provider's capabilities at any given moment. This approach will allow for more resource-efficient and accurate service discovery in mobile systems and will enable more reliable provider functionality in mobile devices

A Survey on Service Composition Middleware in Pervasive Environments

The development of pervasive computing has put the light on a challenging problem: how to dynamically compose services in heterogeneous and highly changing environments? We propose a survey that defines the service composition as a sequence of four steps: the translation, the generation, the evaluation, and finally the execution. With this powerful and simple model we describe the major service composition middleware. Then, a classification of these service composition middleware according to pervasive requirements - interoperability, discoverability, adaptability, context awareness, QoS management, security, spontaneous management, and autonomous management - is given. The classification highlights what has been done and what remains to do to develop the service composition in pervasive environments

Bridging between sensor measurements and symbolic ontologies through conceptual spaces

The increasing availability of sensor data through a variety of sensor-driven devices raises the need to exploit the data observed by sensors with the help of formally specified knowledge representations, such as the ones provided by the Semantic Web. In order to facilitate such a Semantic Sensor Web, the challenge is to bridge between symbolic knowledge representations and the measured data collected by sensors. In particular, one needs to map a given set of arbitrary sensor data to a particular set of symbolic knowledge representations, e.g. ontology instances. This task is particularly challenging due to the potential infinite variety of possible sensor measurements. Conceptual Spaces (CS) provide a means to represent knowledge in geometrical vector spaces in order to enable computation of similarities between knowledge entities by means of distance metrics. We propose an ontology for CS which allows to refine symbolic concepts as CS and to ground instances to so-called prototypical members described by vectors. By computing similarities in terms of spatial distances between a given set of sensor measurements and a finite set of prototypical members, the most similar instance can be identified. In that, we provide a means to bridge between the real-world as observed by sensors and symbolic representations. We also propose an initial implementation utilizing our approach for measurement-based Semantic Web Service discovery

Non-functional Property based service selection: A survey and classification of approaches

In recent years there has been much effort dedicated to developing approaches for service selection based on non-functional properties. It is clear that much progress has been made, and by considering the individual approaches there is some overlap in functionality, but obviously also some divergence. In this paper we contribute a classification of approaches, that is, we define a number of criteria which allow to differentiate approaches. We use this classification to provide a comparison of existing approaches and in that sense provide a survey of the state of the art of the field. Finally we make some suggestions as to where the research in this area might be heading and which new challenges need to be addressed