Abstract
Fog computing is intended for distributed computing where numerous “peripheral” devices connect to a cloud. Many of these devices generate voluminous raw data, and rather than forward all this data to cloud servers to be processed, Fog computing stipulates to do as much processing as possible using computing units co-located with the data-generating devices, so that processed data instead of raw data is forwarded. Moreover, processed data is most likely to be needed by the same devices that generated it, so latency between input and response is minimized. This paper proposes a new technique for resource allocation in a Fog computing environment aiming to optimally serve the service requests generated by IoT objects. We adapt the proven Gale-Shapley matching algorithm and then implement it within a simulation environment. Then, we give a discussion and analysis of experimental results.
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Hammal, A., Lerari, M., Zeraoulia, K., Hammal, Y. (2023). An Efficient Resource Allocation Technique in a Fog Computing Environment. In: Abraham, A., Pllana, S., Casalino, G., Ma, K., Bajaj, A. (eds) Intelligent Systems Design and Applications. ISDA 2022. Lecture Notes in Networks and Systems, vol 717. Springer, Cham. https://doi.org/10.1007/978-3-031-35510-3_52
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DOI: https://doi.org/10.1007/978-3-031-35510-3_52
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