On Edge-Fog-Cloud Collaboration and Reaping Its Benefits: A Heterogeneous Multi-Tier Edge Computing Architecture
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-ti...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-01-01
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| Series: | Future Internet |
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| Online Access: | https://www.mdpi.com/1999-5903/17/1/22 |
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| author | Niroshinie Fernando Samir Shrestha Seng W. Loke Kevin Lee |
| author_facet | Niroshinie Fernando Samir Shrestha Seng W. Loke Kevin Lee |
| author_sort | Niroshinie Fernando |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-51646b3772c7408097df0769f682513d |
| institution | Kabale University |
| issn | 1999-5903 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Future Internet |
| spelling | doaj-art-51646b3772c7408097df0769f682513d2025-01-24T13:33:35ZengMDPI AGFuture Internet1999-59032025-01-011712210.3390/fi17010022On Edge-Fog-Cloud Collaboration and Reaping Its Benefits: A Heterogeneous Multi-Tier Edge Computing ArchitectureNiroshinie Fernando0Samir Shrestha1Seng W. Loke2Kevin Lee3School of Information Technology, Deakin University, Geelong, VIC 3220, AustraliaSchool of Information Technology, Deakin University, Geelong, VIC 3220, AustraliaSchool of Information Technology, Deakin University, Geelong, VIC 3220, AustraliaSchool of Information Technology, Deakin University, Geelong, VIC 3220, AustraliaEdge, 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.https://www.mdpi.com/1999-5903/17/1/22edge computingfog computingcloud computingdevice-enhanced edge |
| spellingShingle | Niroshinie Fernando Samir Shrestha Seng W. Loke Kevin Lee On Edge-Fog-Cloud Collaboration and Reaping Its Benefits: A Heterogeneous Multi-Tier Edge Computing Architecture Future Internet edge computing fog computing cloud computing device-enhanced edge |
| title | On Edge-Fog-Cloud Collaboration and Reaping Its Benefits: A Heterogeneous Multi-Tier Edge Computing Architecture |
| title_full | On Edge-Fog-Cloud Collaboration and Reaping Its Benefits: A Heterogeneous Multi-Tier Edge Computing Architecture |
| title_fullStr | On Edge-Fog-Cloud Collaboration and Reaping Its Benefits: A Heterogeneous Multi-Tier Edge Computing Architecture |
| title_full_unstemmed | On Edge-Fog-Cloud Collaboration and Reaping Its Benefits: A Heterogeneous Multi-Tier Edge Computing Architecture |
| title_short | On Edge-Fog-Cloud Collaboration and Reaping Its Benefits: A Heterogeneous Multi-Tier Edge Computing Architecture |
| title_sort | on edge fog cloud collaboration and reaping its benefits a heterogeneous multi tier edge computing architecture |
| topic | edge computing fog computing cloud computing device-enhanced edge |
| url | https://www.mdpi.com/1999-5903/17/1/22 |
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