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Energy Efficient Resource Scheduling Using Optimization Based Neural Network in Mobile Cloud Computing
P. Akki,
Published in Springer
2020
Volume: 114
   
Issue: 2
Pages: 1785 - 1804
Abstract
The mobile cloud computing has become an emerging technology where the mobile computing is integrated with cloud computing to process the mobile data. Besides the advantages of mobile cloud computing, there are some issues which include power consumption, resource scarcity, quality of service, security and computational cost. In this paper, in order to minimize total power consumption with better performance, the neural network based optimization methods using artificial neural network and convolutional neural network models were implemented by varying variance and loudness. From the experimental results it is observed that, by using optimization in the neural network, the power consumption has been reduced by 53.68% and obtained improvement using convolutional neural network which further reduced the power consumption by 30.3% with minimum root mean square error compared with other algorithms. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.
About the journal
JournalData powered by TypesetWireless Personal Communications
PublisherData powered by TypesetSpringer
ISSN09296212