An intelligent admission control manager in Fog Cloud, A hybrid machine learning approach

What is it about?

In this work, an intelligent admission control manager is being proposed for placing the request based on the parameters such as CPU, memory, storage besides few other categorical parameters, for example, job priority and time sensitivity. The proposed work applies machine intelligence techniques, clustering for labeling the applications’ requests followed by a decision tree, using the labeled requests, to classify the incoming requests.

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Photo by Kevin Ku on Unsplash

Photo by Kevin Ku on Unsplash

Why is it important?

The integration of IoT, fog, and cloud requires intelligent admission control strategies to facilitate resource scheduling and allocation. The proposed work is a step toward this. The results are very encouraging and prove the effectiveness of the proposed work. It shows that the proposed scheme classifies the computing nodes well and allocates the requests to the appropriate computing nodes. The proposed work has full potential to be included in the future system of fog-integrated cloud.

Perspectives