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On Edge-Fog-Cloud Collaboration and Reaping Its Benefits: A Heterogeneous Multi-Tier Edge Computing Architecture

Author

Listed:
  • Niroshinie Fernando

    (School of Information Technology, Deakin University, Geelong, VIC 3220, Australia)

  • Samir Shrestha

    (School of Information Technology, Deakin University, Geelong, VIC 3220, Australia)

  • Seng W. Loke

    (School of Information Technology, Deakin University, Geelong, VIC 3220, Australia)

  • Kevin Lee

    (School of Information Technology, Deakin University, Geelong, VIC 3220, Australia)

Abstract

Edge, fog, and cloud computing provide complementary capabilities to enable distributed processing of IoT data. This requires offloading mechanisms, decision-making mechanisms, support for the dynamic availability of resources, and the cooperation of available nodes. This paper proposes a novel 3-tier architecture that integrates edge, fog, and cloud computing to harness their collective strengths, facilitating optimised data processing across these tiers. Our approach optimises performance, reducing energy consumption, and lowers costs. We evaluate our architecture through a series of experiments conducted on a purpose-built testbed. The results demonstrate significant improvements, with speedups of up to 7.5 times and energy savings reaching 80%, underlining the effectiveness and practical benefits of our cooperative edge-fog-cloud model in supporting the dynamic computational needs of IoT ecosystems. We argue that a multi-tier (e.g., edge-fog-cloud) dynamic task offloading and management of heterogeneous devices will be key to flexible edge computing, and that the advantage of task relocation and offloading is not straightforward but depends on the configuration of devices and relative device capabilities.

Suggested Citation

  • Niroshinie Fernando & Samir Shrestha & Seng W. Loke & Kevin Lee, 2025. "On Edge-Fog-Cloud Collaboration and Reaping Its Benefits: A Heterogeneous Multi-Tier Edge Computing Architecture," Future Internet, MDPI, vol. 17(1), pages 1-23, January.
    • Handle: RePEc:gam:jftint:v:17:y:2025:i:1:p:22-:d:1561423
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