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A Framework for Cloud Selection Based on Business Process Profile

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Information Systems (EMCIS 2017)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 299))

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Abstract

The lack of a system that assists in the business process out-sourcing to the cloud hinders the widespread adoption of this emerging computing paradigm. To the best of our knowledge, there is no system that has tackled the business process outsourcing to the cloud issues such as selecting the activities to outsource and the cloud services to support their execution based on objective and subjective assessments of cloud services. In this paper, we propose a system tackling these issues by using previous cloud users experience for the subjective assessment. The objective assessment is based on simulations using the well-known CloudSim toolkit. The aggregation of the objective and subjective assessment allows for more reliable cloud service selection. Furthermore, we propose an optimal deployment of business process activities by proposing a novel penalty based genetic algorithm while considering business process profile.

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Author information

Authors and Affiliations

  1. Sfax University, Sfax, Tunisia

    Mouna Rekik & Khouloud Boukadi

  2. King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia

    Hanene Ben-Abdallah

  3. Mir@cl Laboratory, Sfax, Tunisia

    Mouna Rekik, Khouloud Boukadi & Hanene Ben-Abdallah

Authors
  1. Mouna Rekik
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  2. Khouloud Boukadi
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  3. Hanene Ben-Abdallah
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Corresponding author

Correspondence to Mouna Rekik .

Editor information

Editors and Affiliations

  1. Department of Digital Systems, University of Piraeus, Piraeus, Greece

    Marinos Themistocleous

  2. Department of Management and Technology, Bocconi University, Milan, Italy

    Vincenzo Morabito

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Rekik, M., Boukadi, K., Ben-Abdallah, H. (2017). A Framework for Cloud Selection Based on Business Process Profile. In: Themistocleous, M., Morabito, V. (eds) Information Systems. EMCIS 2017. Lecture Notes in Business Information Processing, vol 299. Springer, Cham. https://doi.org/10.1007/978-3-319-65930-5_8

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  • DOI: https://doi.org/10.1007/978-3-319-65930-5_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-65929-9

  • Online ISBN: 978-3-319-65930-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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