IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v12y2020i5p89-d358964.html
   My bibliography  Save this article

Modeling and Simulation Tools for Fog Computing—A Comprehensive Survey from a Cost Perspective

Author

Listed:
  • Spiridoula V. Margariti

    (Department of Informatics and Telecommunications, University of Ioannina, GR-47100 Arta, Greece)

  • Vassilios V. Dimakopoulos

    (Department of Computer Science and Engineering, University of Ioannina, GR-45110 Ioannina, Greece)

  • Georgios Tsoumanis

    (Department of Informatics and Telecommunications, University of Ioannina, GR-47100 Arta, Greece)

Abstract

Fog computing is an emerging and evolving technology, which bridges the cloud with the network edges, allowing computing to work in a decentralized manner. As such, it introduces a number of complex issues to the research community and the industry alike. Both of them have to deal with many open challenges including architecture standardization, resource management and placement, service management, Quality of Service (QoS), communication, participation, to name a few. In this work, we provide a comprehensive literature review along two axes— modeling with an emphasis in the proposed fog computing architectures and simulation which investigates the simulation tools which can be used to develop and evaluate novel fog-related ideas.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jftint:v:12:y:2020:i:5:p:89-:d:358964
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/12/5/89/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1999-5903/12/5/89/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    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. Saurabh Shukla & Mohd Fadzil Hassan & Muhammad Khalid Khan & Low Tang Jung & Azlan Awang, 2019. "An analytical model to minimize the latency in healthcare internet-of-things in fog computing environment," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-31, November.
    4. Lykke E. Andersen & Anna Sophia Doyle & Fabián E. Soria & Montserrat Valdivia, 2016. "I - Internet," INESAD book chapters, in: Lykke E. Andersen & Boris Branisa & Stefano Canelas (ed.), El ABC del desarrollo en Bolivia, edition 1, volume 1, chapter 0, pages 101-106, Institute for Advanced Development Studies.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dilger, Alexander, 2016. "Aktuelle Probleme der EU," Discussion Papers of the Institute for Organisational Economics 04/2016, University of Münster, Institute for Organisational Economics.
    2. Konstantinos Ioannou & Dimitrios Myronidis, 2021. "Automatic Detection of Photovoltaic Farms Using Satellite Imagery and Convolutional Neural Networks," Sustainability, MDPI, vol. 13(9), pages 1-15, May.
    3. 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.
    4. 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.
    5. Agbonaye, Osaru & Keatley, Patrick & Huang, Ye & Ademulegun, Oluwasola O. & Hewitt, Neil, 2021. "Mapping demand flexibility: A spatio-temporal assessment of flexibility needs, opportunities and response potential," Applied Energy, Elsevier, vol. 295(C).
    6. Khalid Mohiuddin & Huda Fatima & Mohiuddin Ali Khan & Mohammad Abdul Khaleel & Zeenat Begum & Sajid Ali Khan & Omer Bin Hussain, 2023. "Design of a Novel Edge-Centric Cloud Architecture for m-Learning Performance Effectiveness by Leveraging Distributed Computing Paradigms’ Potentials," SAGE Open, , vol. 13(3), pages 21582440231, August.
    7. 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.
    8. Stanly Jayaprakash & Manikanda Devarajan Nagarajan & Rocío Pérez de Prado & Sugumaran Subramanian & Parameshachari Bidare Divakarachari, 2021. "A Systematic Review of Energy Management Strategies for Resource Allocation in the Cloud: Clustering, Optimization and Machine Learning," Energies, MDPI, vol. 14(17), pages 1-18, August.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. Ritika Raj Krishna & Aanchal Priyadarshini & Amitkumar V. Jha & Bhargav Appasani & Avireni Srinivasulu & Nicu Bizon, 2021. "State-of-the-Art Review on IoT Threats and Attacks: Taxonomy, Challenges and Solutions," Sustainability, MDPI, vol. 13(16), pages 1-46, August.
    14. Meena Kumari Kolli & Christian Opp & Daniel Karthe & Nallapaneni Manoj Kumar, 2022. "Web-Based Decision Support System for Managing the Food–Water–Soil–Ecosystem Nexus in the Kolleru Freshwater Lake of Andhra Pradesh in South India," Sustainability, MDPI, vol. 14(4), pages 1-13, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jftint:v:12:y:2020:i:5:p:89-:d:358964. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.