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Abstract. Middleware has emerged as an important architectural component in supporting distributed applications. With the expanding role of middleware, however, a number of problems are emerging. Most significantly, it is becoming difficult for a single solution to meet the requirements of a range of application domains. Hence, the paper argues that the next generation of middleware platforms should be both configurable and re-configurable. Furthermore, it is claimed that reflection offers a principled means of achieving these goals. The paper then presents an architecture for reflective middleware based on a multi-model approach. The main emphasis of the paper is on resource management within this architecture (accessible through one of the meta-models). Through a number of worked examples, we demonstrate that the approach can support introspection, and fine-and coarse-grained adaptation of the resource management framework. We also illustrate how we can achieve multi-faceted adaptation, spanning multiple meta-models.

The goal of the ongoing project described in this paper is to provide an object oriented realtime industrial messaging service on top of a Quality of Service (QoS) aware Object Request Broker (ORB) with real time network communications. Our project has investigated object oriented solutions for industrial messaging services. The corresponding prototype offers a portable object oriented industrial messaging service implemented in Java. We have built a QoS aware extension of this service based on Jonathan, a flexible ORB that allows the introduction of temporal QoS to handle real time constraints. The full prototype is based on the AJAX toolkit, our binding factory for ATM networks.

Abstract. It is quite common these days for experts, casual analysts, executives or data enthusiasts, to analyze large datasets using userfriendly interfaces on top of Business Intelligence (BI) systems. However, current BI systems do not adequately detect and characterize user interests, which may lead to tedious and unproductive interactions. In this paper, we propose to identify such user interests by characterizing the intent of the interaction with the BI system. With an eye on user modeling for proactive search systems, we identify a set of features for an adequate description of intents, and a similarity measure for grouping intents into coherent interests. We validate experimentally our approach with a user study, where we analyze traces of BI navigation. We show that our similarity measure outperforms a state-of-the-art query similarity measure and yields a very good precision with respect to expressed user interests.

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