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Information Systems Frontiers
Erschienen in: Information Systems Frontiers 6/2017

22.05.2017

Reliable and efficient big service selection

verfasst von: Ling Huang, Qinglin Zhao, Yan Li, Shangguang Wang, Lei Sun, Wu Chou

Erschienen in: Information Systems Frontiers | Ausgabe 6/2017

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Abstract

Big services, both virtual (e.g., cloud services) and physical (e.g., public transportation), are evolving rapidly to handle and deal with big data. By aggregating services from various domains, big services adopt selection schemes to produce composite service solutions that meet customer requirements. However, unlike traditional service selection, a huge number of big services require some lengthy selection processes to improve the service reliability. In this paper, we propose an efficient big service selection approach based on the coefficient of variation and mixed integer programming that improves the solution in two senses: 1) minimizing the time cost and 2) maximizing the reliability. We tested our approach on real-world datasets, and the experimental results indicated that our approach is superior to others.
Vorheriger Artikel How user relationships affect user perceived value propositions of enterprises on social commerce platforms
Nächster Artikel The design of a cloud-based tracker platform based on system-of-systems service architecture

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Metadaten
Titel
Reliable and efficient big service selection
verfasst von
Ling Huang
Qinglin Zhao
Yan Li
Shangguang Wang
Lei Sun
Wu Chou
Publikationsdatum
22.05.2017
Verlag
Springer US
Erschienen in
Information Systems Frontiers / Ausgabe 6/2017
Print ISSN: 1387-3326
Elektronische ISSN: 1572-9419
DOI
https://doi.org/10.1007/s10796-017-9767-x

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