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A fuzzy approach for optimal placement of IoT applications in fog-cloud computing

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Abstract

Fog-cloud computing is a promising distributed model for hosting ever-increasing Internet of Things (IoT) applications. IoT applications should meet different characteristics such as deadline, frequency rate, and input file size. Fog nodes are heterogeneous, resource-limited devices and cannot accommodate all the IoT applications. Due to these difficulties, designing an efficient algorithm to deploy a set of IoT applications in a fog-cloud environment is very important. In this paper, a fuzzy approach is developed to classify applications based on their characteristics then an efficient heuristic algorithm is proposed to place applications on the virtualized computing resources. The proposed policy aims to provide a high quality of service for IoT users while the profit of fog service providers is maximized by minimizing resource wastage. Extensive simulation experiments are conducted to evaluate the performance of the proposed policy. Results show that the proposed policy outperforms other approaches by improving the average response time up to 13%, the percentage of deadline satisfied requests up to 12%, and the resource wastage up to 26%.

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The authors declare that all data supporting the findings of this study are available within the article.

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Funding

No funds, Grants, or other support was received.

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Authors and Affiliations

  1. Department of Computer Engineering, Sanandaj Branch, Islamic Azad University, Sanandaj, Iran

    Farhad Tavousi & Abdulbaghi Ghaderzadeh

  2. Department of Computer Engineering and IT, University of Kurdistan, Sanandaj, Iran

    Sadoon Azizi

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  1. Farhad Tavousi
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  2. Sadoon Azizi
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  3. Abdulbaghi Ghaderzadeh
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All authors contributed to the study conception and design. All authors read and approved the final manuscript.

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Correspondence to Abdulbaghi Ghaderzadeh.

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Tavousi, F., Azizi, S. & Ghaderzadeh, A. A fuzzy approach for optimal placement of IoT applications in fog-cloud computing. Cluster Comput 25, 303–320 (2022). https://doi.org/10.1007/s10586-021-03406-0

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  • DOI: https://doi.org/10.1007/s10586-021-03406-0

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