| Autor: |
Zeraoulia, Khaled, Hammal, Ayoub, Lerari, Mehdi, Hammal, Youcef |
| Předmět: |
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| Zdroj: |
International Journal of Computer Information Systems & Industrial Management Applications; 2023, Vol. 15, p97-108, 12p |
| Abstrakt: |
Fog computing is used to expand Cloud computing services at the network edge. A key step in the process of improving Fog services is the management of Fog resources. Fog resources are usually dynamic, heterogeneous, latencyconstrained, and bandwidth-constrained as compared to Cloud resources. Improving the performance of Fog systems requires addressing Fog resource management. Also, in large-scale Fog networks, resource management still faces more difficulties despite these improvements. Towards this end, this paper proposes a new resource allocation technique in a large-scale Fog network to optimally serve the service requests generated by a set of IoT objects. In this technique, we exploit the proven stable and efficient Gale Shapley matching algorithm in large-scale Fog computing networks. IFogSIM is used to demonstrate the effectiveness of this approach. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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