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Deep Learning Approaches for Information - Centric Network and Internet of Things

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Deep Learning Approaches for Information - Centric Network and Internet of Things


Aashay Pawar



Aashay Pawar "Deep Learning Approaches for Information - Centric Network and Internet of Things" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-6, October 2020, pp.492-495, URL: https://www.ijtsrd.com/papers/ijtsrd33346.pdf

Technologies are rapidly increasing with additions to them every single day. Cloud Computing and the Internet of Things (IoT) have become two very closely associated with future internet technologies. One provides a platform to the other for success, the benefits of which could be from computing to processing and analyzing the information to reduce latency for real-time applications. However, there are a few IoT devices that do not support on-device processing. An alternate solution of this is Edge Computing, where the consumers can witness a close call with the computation and services. In this work, we will be to studying and discussing the application of combining Deep Learning with IoT and Information-Centric Networking. A Convolutional Neural Network (CNN) model, a Deep Learning model, can make the most reliable data available from the complex IoT environment. Additionally, some Deep Learning models such as Recurrent Neural Network (RNN) and Reinforcement Learning have also integrated with IoT, which can also collect the information from real-time applications.

Deep Learning, Internet of Things, Edge Computing, Information-Centric Networking


IJTSRD33346
Volume-4 | Issue-6, October 2020
492-495
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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