The service composition problem in Cloud computing is formulated as a multiple criteria decision making problem. Due to the extensive search space, Cloud service composition is addressed as an NP-hard problem. Using a proper dataset is considered one of the main challenges to evaluate the efficiency of the developed service composition algorithms. According to the work in this paper, a new dataset has been introduced, called Integrated Cloud Services Dataset (ICSD). This dataset is constructed by amalgamating the Google cluster-usage traces, and a real QoS dataset. To evaluate the efficiency of the ICSD dataset, a proof of concept has been done by implementing and evaluating an existing Cloud service compositing approach; PSO algorithm with skyline operator using ICSD dataset. According to the implementation results, it is found that the ICSD dataset achieved a high degree of optimality with low time complexity, which significantly increases the ICSD dataset accuracy in Cloud services composition environment.
CITATION STYLE
Haytamy, S. S., Kholidy, H. A., & Omara, F. A. (2018). ICSD: Integrated cloud services dataset. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10975 LNCS, pp. 18–30). Springer Verlag. https://doi.org/10.1007/978-3-319-94472-2_2
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