A Framework for Trusted Services

An existing challenge when selecting services to be used in a service- based system is to be able to distinguish between good and bad services. In this paper we present a trust-based service selection framework. The framework uses a trust model that calculates the level of trust a user may have with a service based on past experience of the user with the service and feedback about the service received from other users. The model takes into account different levels of trust among users, different relationships between users, and different levels of importance that a user may have for certain quality aspects of a service. A prototype tool has been implemented to illustrate and evaluate the work. The trust model has been evaluated in terms of its capacity to adjust itself due to changes in user ratings and its robustness

Design of a framework for automated service mashup creation and execution based on semantic reasoning

Instead of building self-contained silos, applications are being broken down in independent structures able to offer a scoped service using open communication standards and encoding. Nowadays there is no automatic environment for the construction of new mashups from these reusable services. At the same time the designer of the mashup needs to establish the actual locations for deployment of the different components. This paper introduces the development of a framework focusing on the dynamic creation and execution of service mashups. By enriching the available building blocks with semantic descriptions, new service mashups are automatically composed through the use of planning algorithms. The composed mashups are automatically deployed on the available resources making optimal use of bandwidth, storage and computing power of the network and server elements. The system is extended with dynamic recovery from resource and network failures. This enrichment of business components and services with semantics, reasoning, and distributed deployment is demonstrated by means of an e-shop use case

Cognitively-inspired Agent-based Service Composition for Mobile & Pervasive Computing

Automatic service composition in mobile and pervasive computing faces many challenges due to the complex and highly dynamic nature of the environment. Common approaches consider service composition as a decision problem whose solution is usually addressed from optimization perspectives which are not feasible in practice due to the intractability of the problem, limited computational resources of smart devices, service host's mobility, and time constraints to tailor composition plans. Thus, our main contribution is the development of a cognitively-inspired agent-based service composition model focused on bounded rationality rather than optimality, which allows the system to compensate for limited resources by selectively filtering out continuous streams of data. Our approach exhibits features such as distributedness, modularity, emergent global functionality, and robustness, which endow it with capabilities to perform decentralized service composition by orchestrating manifold service providers and conflicting goals from multiple users. The evaluation of our approach shows promising results when compared against state-of-the-art service composition models.Comment: This paper will appear on AIMS'19 (International Conference on Artificial Intelligence and Mobile Services) on June 2