Dynamic Traffic Prediction with Adaptive Sampling for 5G HetNet IoT Applications
Joint Authors
Wu, Shuangli
Mao, Wei
Liu, Cong
Tang, Tao
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-06-26
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Information Technology and Computer Science
Abstract EN
Due to the proliferation of global monitoring sensors, the Internet of Things (IoT) is widely used to build smart cities and smart homes.
5G HetNets play an important role in the IoT video stream.
This paper proposes an improved Call Session Control Function (CSCF) scheme.
The improved CSCF server contains additional modules to facilitate IoT traffic prediction and resource reservation.
We highlight traffic prediction in this work and develop a compressed sensing based linear predictor to catch the traffic patterns.
Experimental results justify that our proposed scheme can forecast the traffic load with high accuracy but low sampling overhead.
American Psychological Association (APA)
Wu, Shuangli& Mao, Wei& Liu, Cong& Tang, Tao. 2019. Dynamic Traffic Prediction with Adaptive Sampling for 5G HetNet IoT Applications. Wireless Communications and Mobile Computing،Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1212135
Modern Language Association (MLA)
Wu, Shuangli…[et al.]. Dynamic Traffic Prediction with Adaptive Sampling for 5G HetNet IoT Applications. Wireless Communications and Mobile Computing No. 2019 (2019), pp.1-11.
https://search.emarefa.net/detail/BIM-1212135
American Medical Association (AMA)
Wu, Shuangli& Mao, Wei& Liu, Cong& Tang, Tao. Dynamic Traffic Prediction with Adaptive Sampling for 5G HetNet IoT Applications. Wireless Communications and Mobile Computing. 2019. Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1212135
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1212135
