Abstract
This paper presents a multi-criteria cloud-fog coordination model to recommend where data that things generate should be sent (either cloud, fog, or cloud & fog concurrently) and in what order (either cloud then fog, fog then cloud, or fog & cloud concurrently). The model considers end-users’ concerns such as data latency, sensitivity, and freshness. The coordination model uses fuzzy logic when addressing these concerns in preparation for producing the recommendations. For validation purposes, a healthcare-driven IoT application along with an in-house testbed, that features real sensors and fog and cloud platforms, have permitted to carry out different experiments that demonstrate the technical feasibility of both the multi-criteria cloud-fog coordination model and the fuzzy-logic-based approach.
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Notes
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- 2.
Processing data at cloud nodes is different from processing data at fog nodes.
- 3.
Pre-processing data at cloud nodes prior to sending the obtained data to fog nodes.
- 4.
Pre-processing data at fog nodes prior to sending the obtained data to cloud nodes.
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- 6.
T \(\rightarrow \) C|F coordination has been discarded; it does not fit into the case study.
- 7.
In the case of T \(\rightarrow \) F, the time is multiplied by xin[10; 100], for the sake of representation.
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Yahya, F., Maamar, Z., Boukadi, K. (2020). A Multi-Criteria Decision Making Approach for Cloud-Fog Coordination. In: Barolli, L., Amato, F., Moscato, F., Enokido, T., Takizawa, M. (eds) Advanced Information Networking and Applications. AINA 2020. Advances in Intelligent Systems and Computing, vol 1151. Springer, Cham. https://doi.org/10.1007/978-3-030-44041-1_99
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