A Deep Learning Approach for Energy Efficient Computational Offloading in Mobile Edge Computing

A Deep Learning Approach for Energy Efficient Computational Offloading in Mobile Edge Computing

Mobile edge computing (MEC) has shown tremendous potential as a means for computationally intensive mobile applications by partially or entirely offloading computations to a nearby server to minimize the energy consumption of user equipment (UE). However, the task of selecting an optimal set of comp...

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Bibliographic Details
Main Authors: Zaiwar Ali, Lei Jiao, Thar Baker, Ghulam Abbas, Ziaul Haq Abbas, Sadia Khaf
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Computational offloading
deep learning
energy efficient offloading
mobile edge computing
user equipment
Online Access:https://ieeexplore.ieee.org/document/8866714/

Internet

https://ieeexplore.ieee.org/document/8866714/

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