A MULTI-STAGE RECURRENT NEURAL NETWORKS FRAMEWORK FOR IMPROVING RESOURCE ALLOCATION IN CLOUD

ICTACT Journal on Data Science and Machine Learning ( Volume: 1 , Issue: 2 )

Abstract

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The study strives to expand the virtualization technique to create a method that employs efficient architecture and algorithm for enhancing the flexibility and the resource allocation effectiveness of future cloud computing. This method uses Recurrent Neural Networks (RNN) to improve the resource allocation. For this purpose, simulation is done and results are obtained using the GreenCloud Simulator software. The results show that the proposed framework is 20% more efficient than the current QoS improvement framework.

Authors

S Vimalnath
Paavai Engineering College, India

Keywords

Cloud Computing, Quality of Service, Virtualization

Published By
ICTACT
Published In
ICTACT Journal on Data Science and Machine Learning
( Volume: 1 , Issue: 2 )
Date of Publication
March 2020
Pages
59-63
DOI

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