Congestion Control for Machine-Type Communications in LTE-A Networks

Chia-Wei Chang; Yi-Hao Lin; Yi Ren; Jyh-Cheng Chen

doi:10.1109/GLOCOM.2016.7841680

Congestion Control for Machine-Type Communications in LTE-A Networks

Chia-Wei Chang, Yi-Hao Lin, Yi Ren, Jyh-Cheng Chen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

9 Citations (Scopus)

26 Downloads (Pure)

Abstract

Collecting data from a tremendous amount of Internet-of-Things (IoT) devices for next generation networks is a big challenge. A large number of devices may lead to severe congestion in Radio Access Network (RAN) and Core Network (CN). 3GPP has specified several mechanisms to handle the congestion caused by massive amounts of devices. However, detailed settings and strategies of them are not defined in the standards and are left for operators. In this paper, we propose two congestion control algorithms which efficiently reduce the congestion. Simulation results demonstrate that the proposed algorithms can achieve 20~40% improvement regarding accept ratio, overload degree and waiting time compared with those in LTE-A.

Original language	English
Title of host publication	2016 IEEE Global Communications Conference (GLOBECOM)
Publisher	The Institute of Electrical and Electronics Engineers (IEEE)
ISBN (Electronic)	978-1-5090-1328-9
ISBN (Print)	978-1-5090-1329-6
DOIs	https://doi.org/10.1109/GLOCOM.2016.7841680
Publication status	Published - 6 Feb 2017
Event	GLOBECOM 2016 - 2016 IEEE Global Communications Conference - Washington, DC, USA, Washington DC, United States Duration: 4 Dec 2016 → 8 Dec 2016

Conference

Conference	GLOBECOM 2016 - 2016 IEEE Global Communications Conference
Country/Territory	United States
City	Washington DC
Period	4/12/16 → 8/12/16

Access to Document

10.1109/GLOCOM.2016.7841680

Accepted manuscriptAccepted author manuscript, 488 KB

http://ieeexplore.ieee.org/document/7841680/

Edwin Ren
- E.Renuea.acuk
- School of Computing Sciences - Associate Professor in Computing Sciences
- Cyber Security Privacy and Trust Laboratory - Member
- Smart Emerging Technologies - Member
Person: Research Group Member, Academic, Teaching & Research

Cite this

@inproceedings{ef7b81106ac1454f86ee805f9a208e00,

title = "Congestion Control for Machine-Type Communications in LTE-A Networks",

abstract = "Collecting data from a tremendous amount of Internet-of-Things (IoT) devices for next generation networks is a big challenge. A large number of devices may lead to severe congestion in Radio Access Network (RAN) and Core Network (CN). 3GPP has specified several mechanisms to handle the congestion caused by massive amounts of devices. However, detailed settings and strategies of them are not defined in the standards and are left for operators. In this paper, we propose two congestion control algorithms which efficiently reduce the congestion. Simulation results demonstrate that the proposed algorithms can achieve 20~40% improvement regarding accept ratio, overload degree and waiting time compared with those in LTE-A.",

author = "Chia-Wei Chang and Yi-Hao Lin and Yi Ren and Jyh-Cheng Chen",

year = "2017",

month = feb,

day = "6",

doi = "10.1109/GLOCOM.2016.7841680",

language = "English",

isbn = "978-1-5090-1329-6",

booktitle = "2016 IEEE Global Communications Conference (GLOBECOM)",

publisher = "The Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "GLOBECOM 2016 - 2016 IEEE Global Communications Conference ; Conference date: 04-12-2016 Through 08-12-2016",

}

Chang, C-W, Lin, Y-H, Ren, Y & Chen, J-C 2017, Congestion Control for Machine-Type Communications in LTE-A Networks. in 2016 IEEE Global Communications Conference (GLOBECOM). The Institute of Electrical and Electronics Engineers (IEEE), GLOBECOM 2016 - 2016 IEEE Global Communications Conference, Washington DC, United States, 4/12/16. https://doi.org/10.1109/GLOCOM.2016.7841680

TY - GEN

T1 - Congestion Control for Machine-Type Communications in LTE-A Networks

AU - Chang, Chia-Wei

AU - Lin, Yi-Hao

AU - Ren, Yi

AU - Chen, Jyh-Cheng

PY - 2017/2/6

Y1 - 2017/2/6

N2 - Collecting data from a tremendous amount of Internet-of-Things (IoT) devices for next generation networks is a big challenge. A large number of devices may lead to severe congestion in Radio Access Network (RAN) and Core Network (CN). 3GPP has specified several mechanisms to handle the congestion caused by massive amounts of devices. However, detailed settings and strategies of them are not defined in the standards and are left for operators. In this paper, we propose two congestion control algorithms which efficiently reduce the congestion. Simulation results demonstrate that the proposed algorithms can achieve 20~40% improvement regarding accept ratio, overload degree and waiting time compared with those in LTE-A.

AB - Collecting data from a tremendous amount of Internet-of-Things (IoT) devices for next generation networks is a big challenge. A large number of devices may lead to severe congestion in Radio Access Network (RAN) and Core Network (CN). 3GPP has specified several mechanisms to handle the congestion caused by massive amounts of devices. However, detailed settings and strategies of them are not defined in the standards and are left for operators. In this paper, we propose two congestion control algorithms which efficiently reduce the congestion. Simulation results demonstrate that the proposed algorithms can achieve 20~40% improvement regarding accept ratio, overload degree and waiting time compared with those in LTE-A.

U2 - 10.1109/GLOCOM.2016.7841680

DO - 10.1109/GLOCOM.2016.7841680

M3 - Conference contribution

SN - 978-1-5090-1329-6

BT - 2016 IEEE Global Communications Conference (GLOBECOM)

PB - The Institute of Electrical and Electronics Engineers (IEEE)

T2 - GLOBECOM 2016 - 2016 IEEE Global Communications Conference

Y2 - 4 December 2016 through 8 December 2016

ER -

Congestion Control for Machine-Type Communications in LTE-A Networks

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Edwin Ren

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