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Simulating Fog and Edge Computing Scenarios: An Overview and Research Challenges

Author

Listed:
  • Sergej Svorobej

    (Irish Institute of Digital Business, Dublin City University, D9 Dublin, Ireland)

  • Patricia Takako Endo

    (Irish Institute of Digital Business, Dublin City University, D9 Dublin, Ireland)

  • Malika Bendechache

    (Irish Institute of Digital Business, Dublin City University, D9 Dublin, Ireland)

  • Christos Filelis-Papadopoulos

    (Information Technologies Institute, Centre for Research and Technology Hellas, 57001 Thessaloniki, Greece)

  • Konstantinos M. Giannoutakis

    (Information Technologies Institute, Centre for Research and Technology Hellas, 57001 Thessaloniki, Greece)

  • George A. Gravvanis

    (Department of Electrical and Computer Engineering, Democritus University of Thrace, University Campus, Kimmeria, 67100 Xanthi, Greece)

  • Dimitrios Tzovaras

    (Information Technologies Institute, Centre for Research and Technology Hellas, 57001 Thessaloniki, Greece)

  • James Byrne

    (Irish Institute of Digital Business, Dublin City University, D9 Dublin, Ireland)

  • Theo Lynn

    (Irish Institute of Digital Business, Dublin City University, D9 Dublin, Ireland)

Abstract

The fourth industrial revolution heralds a paradigm shift in how people, processes, things, data and networks communicate and connect with each other. Conventional computing infrastructures are struggling to satisfy dramatic growth in demand from a deluge of connected heterogeneous end points located at the edge of networks while, at the same time, meeting quality of service levels. The complexity of computing at the edge makes it increasingly difficult for infrastructure providers to plan for and provision resources to meet this demand. While simulation frameworks are used extensively in the modelling of cloud computing environments in order to test and validate technical solutions, they are at a nascent stage of development and adoption for fog and edge computing. This paper provides an overview of challenges posed by fog and edge computing in relation to simulation.

Suggested Citation

  • Sergej Svorobej & Patricia Takako Endo & Malika Bendechache & Christos Filelis-Papadopoulos & Konstantinos M. Giannoutakis & George A. Gravvanis & Dimitrios Tzovaras & James Byrne & Theo Lynn, 2019. "Simulating Fog and Edge Computing Scenarios: An Overview and Research Challenges," Future Internet, MDPI, vol. 11(3), pages 1-15, February.
    • Handle: RePEc:gam:jftint:v:11:y:2019:i:3:p:55-:d:209266
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    Citations

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    Cited by:

    1. Muhammad Junaid & Asadullah Shaikh & Mahmood Ul Hassan & Abdullah Alghamdi & Khairan Rajab & Mana Saleh Al Reshan & Monagi Alkinani, 2021. "Smart Agriculture Cloud Using AI Based Techniques," Energies, MDPI, vol. 14(16), pages 1-15, August.
    2. Majid Ashouri & Fabian Lorig & Paul Davidsson & Romina Spalazzese, 2019. "Edge Computing Simulators for IoT System Design: An Analysis of Qualities and Metrics," Future Internet, MDPI, vol. 11(11), pages 1-12, November.
    3. Malika Bendechache & Sergej Svorobej & Patricia Takako Endo & Theo Lynn, 2020. "Simulating Resource Management across the Cloud-to-Thing Continuum: A Survey and Future Directions," Future Internet, MDPI, vol. 12(6), pages 1-25, May.
    4. Malika Bendechache & Sergej Svorobej & Patricia Takako Endo & Adrian Mihai & Theo Lynn, 2021. "Simulating and Evaluating a Real-World ElasticSearch System Using the RECAP DES Simulator," Future Internet, MDPI, vol. 13(4), pages 1-12, March.
    5. Abderahman Rejeb & John G. Keogh & Horst Treiblmaier, 2019. "Leveraging the Internet of Things and Blockchain Technology in Supply Chain Management," Future Internet, MDPI, vol. 11(7), pages 1-22, July.
    6. Shavan Askar & Zhala Jameel Hamad & Shahab Wahhab Kareem, 2021. "Deep Learning and Fog Computing: A Review," International Journal of Science and Business, IJSAB International, vol. 5(6), pages 197-208.
    7. Spiridoula V. Margariti & Vassilios V. Dimakopoulos & Georgios Tsoumanis, 2020. "Modeling and Simulation Tools for Fog Computing—A Comprehensive Survey from a Cost Perspective," Future Internet, MDPI, vol. 12(5), pages 1-20, May.
    8. Yaghoub Pourasad & Fausto Cavallaro, 2021. "A Novel Image Processing Approach to Enhancement and Compression of X-ray Images," IJERPH, MDPI, vol. 18(13), pages 1-15, June.

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