Abstract. QoS-aware service composition is a key requirement in Service Oriented Computing (SOC) since it enables fulfilling complex user tasks while meeting Quality of Service (QoS) constraints. A challenging issue towards this purpose is the selection of the best set of services to compose, meeting global QoS constraints imposed by the user, which is known to be a NP-hard problem. This challenge becomes even more relevant when it is considered in the context of dynamic service environments. Indeed, two specific issues arise. First, required tasks are fulfilled on the fly, thus the time available for services' selection and composition is limited. Second, service compositions have to be adaptive so that they can cope with changing conditions of the environment. In this paper, we present an efficient service selection algorithm that provides the appropriate ground for QoS-aware composition in dynamic service environments. Our algorithm is formed as a guided heuristic. The paper also presents a set of experiments conducted to evaluate the efficiency of our algorithm, which shows its timeliness and optimality.

In Service Oriented Computing (SOC), modeling the Quality of Service (QoS) is a cornerstone for providing services with quality guarantees. As the technological advances and wide adoption of handheld devices (e.g., PDA and smartphones) and wireless networks (e.g., UMTS, WiFi and Bluetooth) have made service environments more dynamic, QoS models must change accordingly.In this paper, we present a QoS model that provides the approporiate ground for QoS engineering in SOC. Our model focuses on emerging QoS features related to the dynamics of service environments such as user mobility and context awareness of application services. It also considers QoS on an end-to-end basis by covering QoS features of all the resources and actors involved in service provisioning (e.g., network, device, service, end-user). Our model represents QoS with rich semantic information and makes use of the Web Service Quality Model (WSQM) proposed by OASIS.

Service composition is a widely used method in ubiquitous computing that enables accomplishing complex tasks required by users based on elementary (hardware and software) services available in ubiquitous environments. To ensure that users experience the best Quality of Service (QoS) with respect to their quality needs, service composition has to be QoS-aware. Establishing QoS-aware service compositions entails efficient service selection taking into account the QoS requirements of users. A challenging issue towards this purpose is to consider service selection under global QoS requirements (i.e., requirements imposed by the user on the whole task), which is of high computational cost. This challenge is even more relevant when we consider the dynamics, limited computational resources and timeliness constraints of ubiquitous environments.To cope with the above challenge, in this paper we present QASSA, an efficient service selection algorithm that provides the appropriate ground for QoS-aware service composition in ubiquitous environments. The contribution of QASSA is three-fold. First, it formulates service selection under global QoS requirements as a setbased optimisation problem, benefiting from recent proposals in the domain of multi-objective optimisation. Second, QASSA resolves this problem in an efficient way using clustering techniques, namely the K-Means algorithm. Third, QASSA is devised in two versions, viz., centralised and distributed versions, so that it can be executed on top of centralised and decentralised infrastructures in ubiquitous environments. Results of experimental studies are presented to illustrate the timeliness and optimality of QASSA.

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International audienceA versatile ultra high frequency radiofrequency identification (UHF RFID) antenna system is proposed. Spatial, polarization and radiation pattern diversity is demonstrated with a very reduced number of components. The diversity contribution of such an antenna is then characterized in terms of radio coverage in a RFID portal environment. Radio coverage in complex environment is greatly improved compared to the classical geometry