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Distributed Deep Learning-based Offloading for Mobile Edge Computing Networks
Huang, Liang ; Feng, Xu ; Feng, Anqi ; Huang, Yupin ; Qian, Li Ping
Mobile networks and applications, 2022-06, Vol.27 (3), p.1123-1130
[Peer Reviewed Journal]
New York: Springer US
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Title:
Distributed Deep Learning-based Offloading for Mobile Edge Computing Networks
Author:
Huang, Liang
;
Feng, Xu
;
Feng, Anqi
;
Huang, Yupin
;
Qian, Li Ping
Subjects:
Algorithms
;
Bandwidth
;
Bandwidths
;
Communications Engineering
;
Computation offloading
;
Computer Communication Networks
;
Decisions
;
Deep learning
;
Economic models
;
Edge computing
;
Electrical Engineering
;
Energy conservation
;
Energy consumption
;
Engineering
;
Integer programming
;
IT in Business
;
Machine learning
;
Mixed integer
;
Mobile computing
;
Networks
;
Neural networks
;
Optimization
;
Quality of service
;
Quality of service architectures
;
Servers
;
Wireless communications
;
Wireless networks
;
Workloads
Is Part Of:
Mobile networks and applications, 2022-06, Vol.27 (3), p.1123-1130
Description:
This paper studies mobile edge computing (MEC) networks where multiple wireless devices (WDs) choose to offload their computation tasks to an edge server. To conserve energy and maintain quality of service for WDs, the optimization of joint offloading decision and bandwidth allocation is formulated as a mixed integer programming problem. However, the problem is computationally limited by the curse of dimensionality, which cannot be solved by general optimization tools in an effective and efficient way, especially for large-scale WDs. In this paper, we propose a distributed deep learning-based offloading (DDLO) algorithm for MEC networks, where multiple parallel DNNs are used to generate offloading decisions. We adopt a shared replay memory to store newly generated offloading decisions which are further to train and improve all DNNs. Extensive numerical results show that the proposed DDLO algorithm can generate near-optimal offloading decisions in less than one second.
Publisher:
New York: Springer US
Language:
English
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