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A genetic-based approach for service placement in fog computing

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Abstract

The combination of cloud computing with the Internet of Things has made fundamental changes in areas from industry, healthcare, traffic, and transportation to home appliances and even personal lives. Billions of devices and users are connected through these platforms disseminating enormous amounts of data leading to performance degradation, which has generated a demand for prior application placement planning. This paper focuses on the minimization of application delay and network usage by proposing a genetic-based service placement algorithm in fog-cloud environments. Throughout this work, a penalty-based approach to target both the delay and the number of time-consuming cloud placements is introduced, which explores the solution pool as a function of generations. This helps in exploring a wider space at the beginning and gradually intensifying the effect of penalty in the next generations. In a separate phase, the proximity of the applications to the users is taken into account as well. This is done through the chromosome selection process by using a priority value that identifies the proximity of dependent modules. The results of simulations demonstrate that the proposed algorithm achieved improvements regarding delay, network usage, energy consumption, and cost.

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Authors and Affiliations

  1. School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran

    Nazanin Sarrafzade & Reza Entezari-Maleki

  2. INESC-ID, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal

    Leonel Sousa

Authors
  1. Nazanin Sarrafzade
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  2. Reza Entezari-Maleki
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  3. Leonel Sousa
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Correspondence to Reza Entezari-Maleki.

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Sarrafzade, N., Entezari-Maleki, R. & Sousa, L. A genetic-based approach for service placement in fog computing. J Supercomput 78, 10854–10875 (2022). https://doi.org/10.1007/s11227-021-04254-w

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