Runtime QoS control and revenue optimization within service oriented architecture

The paradigms of service-oriented computing (SOC) and its underlying service-oriented architecture (SOA) have changed the way software applications are designed, developed, deployed, and consumed. Software engineers can therefore realize applications by service composition, using services offered by third parties and the commercial success of composite service providers (CSP) is directly related to their ability to offer services at sharp price/quality ratios. This raises the need to realize desired client perceived Quality of Service (QoS) levels at minimal cost. The problem of controlling QoS in SOC is complex, and although a plethora of well-known QoS-control mechanisms exists for “atomic” Web services used for the composition, it remains a challenge how to exploit these mechanisms for QoS-control in SOA in a cost-effective way. The potential for composite service providers to realize cost savings and/or revenue improvements by optimizing the QoS-control in SOA has not been exploited much so far. To address this issue, proper modeling of the effects of QoS-control parameters is required, and analysis of these models to derive the optimal settings of the parameters is a natural next step. This thesis contributes models and methods to address these QoS-control issues within SOA. We develop the models of the runtime end-to-end QoS-control mechanisms that are used to satisfy QoS requirements of an individual composite service request (e.g. response time) while optimizing some long-term goal (e.g. expected revenue). These models, based on per-request, per-task service selection, facilitate development of simple, yet effective optimal decision-making policies in order to satisfy specified QoS levels. We demonstrate the effectiveness of the developed solutions as well as significant revenue improvements by extensive numerical experiments. The derived policies have negligible overhead with respect to the decision-making process and control actions to be taken by the CSP. The control actions may be automated, and allow for fast reactions to the changes in the volatile service execution environment. In our view this thesis presents a significant step forward to envisioned autonomous, economically profitable systems of services and applications of the future. Our approach opens many interesting opportunities for further research in the challenging area of QoS-control of such “system of systems”.