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A Survey on the Quality of Service and Metaheuristic Based Resolution Methods for Multi-cloud IoT Service Selection

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Innovations in Bio-Inspired Computing and Applications (IBICA 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 419))

Abstract

The Internet-of-Things (IoT) generate increasingly significant amount of data that needs to be stored and analysed. The use of IoT devices as a service makes it more accessible and exploitable, this could be achieved using of cloud computing. Multi-cloud service composition and selection are required to fulfill increasingly complicated user requests for services. A service request is made from a cloud broker to cloud providers (CP) to deliver the required Quality of Service (QoS). Selecting services and optimizing service compositions to satisfy functional and non-functional conflicting requirements across various cloud service providers is an non-deterministic polynomial-time hardness problem (NP-hard). Multiobjective (MO) metaheuristics are known to be performant to solve such a problem. This study examines how to select IoT services to achieve the best performances on the eight selected QoS across multiple CP. The experiment results reveal that among the 18 compared algorithms, the parallel NSGAII provides the most efficient and optimal outcomes.

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Author information

Authors and Affiliations

  1. RIIMA, USTHB, BP 32 El-Alia Bab-Ezzouar, Algiers, Algeria

    Ahmed Zebouchi & Youcef Aklouf

Authors
  1. Ahmed Zebouchi
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  2. Youcef Aklouf
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Corresponding author

Correspondence to Ahmed Zebouchi .

Editor information

Editors and Affiliations

  1. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Ajith Abraham

  2. Departamento de Engenharia Informática, Instituto Superior de Engenharia do Port, Porto, Portugal

    Ana Maria Madureira

  3. Department of Construction Management and Real Estate, Vilnius Gediminas Technical University, Vilnius, Lithuania

    Arturas Kaklauskas

  4. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Niketa Gandhi

  5. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Anu Bajaj

  6. Faculty of Information Communication Technology, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Melaka, Malaysia

    Azah Kamilah Muda

  7. Vilnius University, Kaunas, Lithuania

    Dalia Kriksciuniene

  8. Lisbon University Institute, Lisbon, Portugal

    João Carlos Ferreira

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Zebouchi, A., Aklouf, Y. (2022). A Survey on the Quality of Service and Metaheuristic Based Resolution Methods for Multi-cloud IoT Service Selection. In: Abraham, A., et al. Innovations in Bio-Inspired Computing and Applications. IBICA 2021. Lecture Notes in Networks and Systems, vol 419. Springer, Cham. https://doi.org/10.1007/978-3-030-96299-9_40

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