No abstract

The aim of our research is to find an efficient solution to the services QoS optimization problem. This NP-hard problem is well known in the service-oriented computing field: given a business workflow that includes a set of abstract services and a set of concrete service implementations for each abstract service, the goal is to find the optimal combination of concrete services. The majority of recent proposals indicate the Genetic Algorithms (GA) as the best approach for complex workflows. We propose a new approach, based on Differential Evolution (DE) and a new genome encoding. The results show that proposed algorithms converge faster than the existing ones based on Genetic Algorithms with integer genome encoding.

Abstract-The easiest way for a user to express his needs regarding a desired service is to use natural language. The main issues come from the fact that the natural language is incomplete and ambiguous, while the service composition process should lead to valid services. In this paper we propose a natural language service assemblage method based on composition templates (patterns). The use of templates assures that the composition result is always valid. The proposed system, called NLSC (Natural Language Service Composer), was implemented on the top of a service-oriented middleware called WComp and tested in an intelligent home environment.

No abstract

In this paper we propose an ontology based representation of the affective states for context aware applications that allows expressing the complex relations that are among the affective states and between these and the other context elements. This representation is open to map different affective spaces; basic and secondary states relation (using Fuzzy Logic), the relation between these states and other context elements as location, time, person, activity etc. The proposed affective context model is encoded in OWL. Due to difficulties in direct detection of the secondary affective states we propose a method to infer the characteristic values of these states from other context elements' values. The deduces states are used here to improve the behavior of a Context Aware Museum Guide in order to react more intuitively and more intelligent by taking into account the user's affective states.