Abstract
Cloud service composition is usually long term based and economically driven. Services in cloud computing can be categorized into two groups: Application services and Computing Services. Compositions in the application level are similar to the Web service compositions in Service-Oriented Computing. Compositions in the computing level are similar to the task matching and scheduling in grid computing. We consider cloud service composition from end users perspective. We propose Genetic Algorithm-based approach to model the cloud service composition problem. A comparison is given between the proposed composition approach and other existing algorithms such as Integer Linear Programming. The experiment results proved the efficiency of the proposed approach.
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This work was made possible by NPRP grant # 7 - 481-1 - 088 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.
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Kholidy, H.A., Hassan, H., Sarhan, A.M., Erradi, A., Abdelwahed, S. (2015). QoS Optimization for Cloud Service Composition Based on Economic Model. In: Giaffreda, R., et al. Internet of Things. User-Centric IoT. IoT360 2014. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 150. Springer, Cham. https://doi.org/10.1007/978-3-319-19656-5_48
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DOI: https://doi.org/10.1007/978-3-319-19656-5_48
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