3 research outputs found

    Considering Quality of a Service in an Intentional Approach

    No full text
    International audienceThe success of service-based applications is based on service technologies such as Web services. Nevertheless, the benefits of the Service-Oriented Architecture (SOA) remain mainly at the software level, since business people are often unable to fully exploit its benefits due to their unfamiliarity with such software level technology. The intentional Service-Oriented Architecture (iSOA) suggests a move from the function-driven SOA to intention-driven SOA in order to provide service description understandable by business practitioners. However, such transposition from business to implementation level should also consider Quality of Service (QoS) aspects. In this paper, we propose modeling the Quality of intentional Service (QoiS) by introducing the quality goals and their qualitative and quantitative evaluation. We also propose populating the intentional service registry of the iSOA architecture with the QoiS description

    Capturing and using QoS relationships to improve service selection

    Get PDF
    In a Service-Oriented System (SOS), service requesters specify tasks that need to be executed and the quality levels to meet, whereas service providers advertise their services’ capabilities and the quality levels they can reach. Service selectors then match to the relevant tasks, the candidate services that can perform these tasks to the most desirable quality levels. One of the key problems in QoS-aware service selection lies in managing tradeoffs among QoS expectations at runtime, that is, situations in which service requesters specify quality levels that cannot be simultaneously met. We propose a service selection approach that can deal with tradeoffs. The approach consists of: (i) rich QoS models to be used by service requesters when expressing QoS expectations and service providers when describing services’ QoS, and for representing preference and priority relationships between QoS dimensions; and (ii) a multi-criteria decision making technique that uses the models for service selection
    corecore