Abstract. This paper describes SOUPA (Standard Ontology for Ubiquitous and Pervasive Applications) and the use of this ontology in building the Context Broker Architecture (CoBrA). CoBrA is a new agent architecture for supporting pervasive context-aware systems in a smart space environment. The SOUPA ontology is expressed using the Web Ontology Language OWL and includes modular component vocabularies to represent intelligent agents with associated beliefs, desire, and intentions, time, space, events, user profiles, actions, and policies for security and privacy. Central to CoBrA is an intelligent broker agent that exploits ontologies to support knowledge sharing, context reasoning, and user privacy protection. We also describe two prototype systems that we have developed to demonstrate the feasibility and the use of CoBrA. 1.

The growth in knowledge sharing enabled by the (Semantic) Web has made trust an increasingly critical issue. Based on explicit inter-agent trust relations, a trust network emerges on the (Semantic) Web in the knowledge sharing context. The concept of a trust network and its application to knowledge sharing have received recent attention but neither their structural properties (e.g. dynamics, complexity) nor inference mechanisms (e.g. trust discovery, trust evolution, trust propagation) have been well addressed. This paper formalizes trust network inference notions, providing both data and computational models, and suggests an evaluation model for benchmarking. The data model clarifies the data (context, restriction, output) used by trust network inference for knowledge sharing. It also elaborates trust network representation and articulates different types of trust. The computational model reviews graph theory and referral network interpretations of trust network inference and proposes a new one that treats trust network as an emergent property. This new model supports both trust evolution and trust propagation. The evaluation model describes metrics as well as methods to generate test scenarios and data. We argue that this approach is more customizable, flexible and scalable than traditional approaches such as public reputation systems and collaborative filtering. 1.

Abstract. Developing applications that make use of machine-readable knowledge sources as promised by the Semantic Web vision is attracting much of current research interest; this vision is also affecting important trends in Computer Science such as Grid and Mobile computing. In this paper we propose a version of the BDI agent-oriented programming language AgentSpeak that is based on Description Logic (DL). In this approach, the belief base of an agent contains the definition of complex concepts, besides specific factual knowledge. The advantages of combining AgentSpeak with DL are: (i) queries to the belief base are more expressive as their results do not rely only on explicit knowledge but can be inferred from the ontology; (ii) the notion of belief update is refined since the (ontological) consistency of a belief addition can be checked; (iii) the search for a plan for handling an event is more flexible as it is not based solely on unification but on the subsumption relation between concepts; and (iv) agents may share knowledge by using ontology languages such as the Ontology Web Language (OWL). Extending agent programming languages with DL can have a significant impact on the development of multi-agent systems for the Semantic Web. 1

This paper gives an overview of pro-active meeting assistants, what they are and when they can be useful. We explain how to develop such assistants with respect to requirement definitions and elaborate on a set of Wizard of Oz experiments, aiming to find out in which form a meeting assistant should operate to be accepted by participants and whether the meeting e#ectiveness and e#ciency can be improved by an assistant at all.

Abstract. This paper presents a system, where a model of the user’s tasks is used for automatic service composition in smart spaces. In the system service modeling is decoupled from resource modeling. We present a model for quality of service (QoS) based service composition, integrating it with our resource management scheme. A component acting on behalf of the user composes the service with the aim of maximizing the QoS for the currently active user task. This functionality is decomposed to the description and determination of static and dynamic QoS. The concept of static QoS refers to the degree of match between the requirements of the user’s active task and the qualities and capabilities of a service composition. Dynamic QoS extends static QoS by taking into account the current state and availability of the resources.

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Abstract — Despite several efforts during the last years, the web model and semantic web technologies have not yet been successfully applied to empower Ubiquitous Computing architectures in order to create knowledge-rich environments populated by interconnected smart devices. In this paper we point out some problems of these previous initiatives and introduce SoaM (Smart Objects Awareness and Adaptation Model), an architecture for designing and seamlessly deploying web-powered context-aware semantic gadgets. Implementation and evaluation details of SoaM are also provided in order to identify future research challenges. Index Terms — Ubiquitous computing, semantic web, semantic devices, ubiquitous web I.

Context-awareness plays a key role in a paradigm shift from traditional desktop styled computing to emerging pervasive computing. Many context-aware systems have been built to achieve the vision of pervasive computing and alleviate the human attention bottleneck; however, these systems are far from real world applications. Quality of context is critical in reducing the gap between existing systems and real-life applications. Aiming to provide the support of quality of context, in this paper, we propose a novel quality model for context information and a context management mechanism for inconsistency resolution. We also build a prototype system to validate our proposed model and mechanism, and to assist the development of contextaware applications. Through our evaluations and case study, context-aware applications can be built with the support of quality of context.

Abstract. Privacy protection is a key requirement for the future pervasive computing systems. This paper describes the design and implementation of a privacy protection framework that exploits the SOUPA policy ontology and its associated policy reasoning algorithm. The SOUPA policy ontology expressed in the Web Ontology Language OWL allows users to define policy rules to permit or forbid actions that attempt to access the users ’ private information. Central to the policy reasoning algorithm is the use of a Description Logic inference engine that reasons over the OWL-DL constructs of the policy ontology. We also show the feasibility of this framework through a prototype of the Context Broker Architecture (CoBrA). 1

In this paper we present a taxonomy for characterizing pervasive applications. This taxonomy focuses on abstracting application characteristics, independent of the characteristics of the middleware or infrastructure that support the application, and provides a controlled vocabulary for thinking about the application. We provide an informal verification for the taxonomy by using it to categorize a range of pervasive applications, culled from the literature and from projects we are involved in, and showing that the taxonomy is (a) consistent and complete- similar applications are categorized similarly and applications that are different are not similarly categorized and (b) useful each characteristic provides new information about applications not explained by the other characteristics. Finally, we present concrete uses for the taxonomy.