Abstract
Cloud computing is essentially changing the way services are built, provided and consumed. As a paradigm building on a set of combined technologies, it enables service provision through the commoditization of IT assets and on-demand usage patterns. In the emerging era of the Future Internet, clouds aim at facilitating applications that move away from the monolithic approach into an Internet-scale one, thus exploiting information, individual offerings and infrastructures as composite services. In this paper we present an approach for selecting the services (that comprise the composite ones) in order to meet the end-to-end Quality of Service (QoS) requirements. The approach is enhanced with a relevance feedback mechanism that provides additional information with respect to the importance of the content and the service. The latter is performed in an automated way, allowing for user preferences to be considered during the service selection process. We also demonstrate the operation of the implemented approach and evaluate its effectiveness using a real-world scenario, based on a computer vision application.
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Acknowledgements
The publication of this paper has been partly supported by the University of Piraeus Research Center, and by the European Community under grant agreements n° 214777 (IRMOS project) and n° 216465 (SCOVIS project).
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Kyriazis, D., Doulamis, N., Kousiouris, G., Menychtas, A., Themistocleous, M., Vescoukis, V.C. (2016). Employing Relevance Feedback to Embed Content and Service Importance into the Selection Process of Composite Cloud Services. In: Altmann, J., Silaghi, G., Rana, O. (eds) Economics of Grids, Clouds, Systems, and Services. GECON 2015. Lecture Notes in Computer Science(), vol 9512. Springer, Cham. https://doi.org/10.1007/978-3-319-43177-2_7
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DOI: https://doi.org/10.1007/978-3-319-43177-2_7
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