A MULTI-STAGE RECURRENT NEURAL NETWORKS FRAMEWORK FOR IMPROVING RESOURCE ALLOCATION IN CLOUD
Abstract
vioft2nntf2t|tblJournal|Abstract_paper|0xf4ffc6952b000000ca4b000001000a00
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
Yearly Full Views
JanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecember
000000000110
Published By :
ICTACT
Published In :
ICTACT Journal on Data Science and Machine Learning
( Volume: 1 , Issue: 2 , Pages: 59-63 )
Date of Publication :
March 2020
Page Views :
160
Full Text Views :
6

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.