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Towards Scalability Guidelines for Semantic Data Container Management

Authors: G. Brataas, B. Neumayr, C. Schütz, A. Vennesland
Paper: Neum18c (2018)
Citation: Companion of the 2018 ACM/SPEC International Conference on Performance Engineering (ICPE 2018), April 9-13, 2018, Berlin, Germany, ACM Press, ISBN 978-1-4503-5629-9, DOI: 10.1145/3185768.3186302, pp. 17-20, 2018.
Resources: Copy  (In order to obtain the copy please send an email with subject  Neum18c  to dke.win@jku.at)


Abstract (English):

Semantic container management is a promising approach to organize data. However, the scalability of this approach is challenging. By scalability in this paper, we mean the expressivity and size of the semantic data containers we can handle, given a suitable quality threshold. In this paper, we derive scalability characteristics of the semantic container approach in a structured way. We also describe actual experiments where we vary the number of available CPU cores and quality thresholds. We conclude this work-in-Progress paper by describing how more measurements could be performed so that the missing guidelines could be provided.