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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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.


This is my first journal publication and will always remains to my close to my heart I have lot of time efforts for it and learned a lot in this journey.

Jawaharlal Nehru University

Read the Original

This page is a summary of: Intelligent admission control manager for fog‐integrated cloud: A hybrid machine learning approach, Concurrency and Computation Practice and Experience, December 2021, Wiley,
DOI: 10.1002/cpe.6687.
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