Paper Info
Title
Transfer Learning-powered Resource Optimization for Green Computing in 5G-Aided Industrial Internet of Things
Abstract
AbstractObjective: Green computing meets the needs of a low-carbon society and it is an important aspect of promoting social sustainable development and technological progress. In the investigation, green computing for resource management and allocation issues is only discussed. Therefore, in the context of the 5G communication network, the investigation of the data classification and resource optimization of the Internet of Things are conducted. Method: The virtualization architecture of the heterogeneous wireless network resource based on 5G technology is designed. The related investigation is conducted based on 5G network and Internet of Things technology. Under the traditional method, the transfer learning is introduced to improve the AdaBoost (Adaptive Boosting) algorithm to classify the data. The investigated complete resource reuse method is used to optimize resources. A method that a sub-channel can be reused by a cellular link and any number of D2D links at the same time is proposed to conduct resource optimization investigation. Results: The investigation indicates that the classification accuracy of the algorithm is excellent for the data classification of the Internet of Things and has different advantages in various aspects compared with other algorithms. The designed algorithm can find a larger set of resource reuse and have a significant increase in spectrum utilization efficiency. Conclusion: The investigation can contribute to the boom in the Internet of Things in terms of data classification and resource optimization based on 5G.
Year
DOI
Venue
2022
10.1145/3434774
ACM Transactions on Internet Technology
Keywords
DocType
Volume
Internet of Things, 5G, resource optimization, data classification, transfer learning, AdaBoost
Journal
22
Issue
ISSN
Citations 
2
1533-5399
0
PageRank 
References 
Authors
0.34
39
4
Name
Order
Citations
PageRank
Zhihan Lu11515136.60
R Lou200.68
Amit Kumar Singh364563.25
Qing Wang434576.64