Adaptive control channel traffic shaping for virtualized SDN in clouds

Yeonho Yoo; Gyeongsik Yang; Minkoo Kang; Chuck Yoo

doi:10.1109/CLOUD49709.2020.00013

Adaptive control channel traffic shaping for virtualized SDN in clouds

Yeonho Yoo, Gyeongsik Yang, Minkoo Kang, Chuck Yoo

Department of Computer Science and Engineering

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

1 Citation (Scopus)

Abstract

As the number of tenants in clouds grows, virtualized SDN faces a challenge of control channel fairness as the control channels interfere with each other. This paper proposes an adaptive traffic shaping scheme for control channels called 'Sincon.' Through experiments, Sincon achieves traffic shaping for control channels and improves the variances of control channel throughputs and forwarding setup times up to 3.8 and 2.86 times, respectively.

Original language	English
Title of host publication	Proceedings - 2020 IEEE 13th International Conference on Cloud Computing, CLOUD 2020
Publisher	IEEE Computer Society
Pages	22-24
Number of pages	3
ISBN (Electronic)	9781728187808
DOIs	https://doi.org/10.1109/CLOUD49709.2020.00013
Publication status	Published - 2020 Oct
Event	13th IEEE International Conference on Cloud Computing, CLOUD 2020 - Virtual, Beijing, China Duration: 2020 Oct 18 → 2020 Oct 24

Publication series

Name	IEEE International Conference on Cloud Computing, CLOUD
Volume	2020-October
ISSN (Print)	2159-6182
ISSN (Electronic)	2159-6190

Conference

Conference	13th IEEE International Conference on Cloud Computing, CLOUD 2020
Country	China
City	Virtual, Beijing
Period	20/10/18 → 20/10/24

Keywords

Cloud network
Control channel traffic
Network virtualization
SDN
Traffic shaping

ASJC Scopus subject areas

Artificial Intelligence
Information Systems
Software

Access to Document

10.1109/CLOUD49709.2020.00013

Fingerprint Dive into the research topics of 'Adaptive control channel traffic shaping for virtualized SDN in clouds'. Together they form a unique fingerprint.

Cite this

Yoo, Y., Yang, G., Kang, M., & Yoo, C. (2020). Adaptive control channel traffic shaping for virtualized SDN in clouds. In Proceedings - 2020 IEEE 13th International Conference on Cloud Computing, CLOUD 2020 (pp. 22-24). [9284327] (IEEE International Conference on Cloud Computing, CLOUD; Vol. 2020-October). IEEE Computer Society. https://doi.org/10.1109/CLOUD49709.2020.00013

Adaptive control channel traffic shaping for virtualized SDN in clouds. / Yoo, Yeonho; Yang, Gyeongsik; Kang, Minkoo; Yoo, Chuck.

Proceedings - 2020 IEEE 13th International Conference on Cloud Computing, CLOUD 2020. IEEE Computer Society, 2020. p. 22-24 9284327 (IEEE International Conference on Cloud Computing, CLOUD; Vol. 2020-October).

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

Yoo, Y, Yang, G, Kang, M & Yoo, C 2020, Adaptive control channel traffic shaping for virtualized SDN in clouds. in Proceedings - 2020 IEEE 13th International Conference on Cloud Computing, CLOUD 2020., 9284327, IEEE International Conference on Cloud Computing, CLOUD, vol. 2020-October, IEEE Computer Society, pp. 22-24, 13th IEEE International Conference on Cloud Computing, CLOUD 2020, Virtual, Beijing, China, 20/10/18. https://doi.org/10.1109/CLOUD49709.2020.00013

@inproceedings{b5c631f7beda43299e5120aab284b4f6,

title = "Adaptive control channel traffic shaping for virtualized SDN in clouds",

abstract = "As the number of tenants in clouds grows, virtualized SDN faces a challenge of control channel fairness as the control channels interfere with each other. This paper proposes an adaptive traffic shaping scheme for control channels called 'Sincon.' Through experiments, Sincon achieves traffic shaping for control channels and improves the variances of control channel throughputs and forwarding setup times up to 3.8 and 2.86 times, respectively.",

keywords = "Cloud network, Control channel traffic, Network virtualization, SDN, Traffic shaping",

author = "Yeonho Yoo and Gyeongsik Yang and Minkoo Kang and Chuck Yoo",

note = "Funding Information: ‡This work was partly supported by Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (No. 2015-0-00280, (SW Starlab) Next generation cloud infra-software toward the guarantee of performance and security SLA) and by Next Generation Engineering Researcher Program of National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT (No. NRF-2019H1D8A2105513).; 13th IEEE International Conference on Cloud Computing, CLOUD 2020 ; Conference date: 18-10-2020 Through 24-10-2020",

year = "2020",

month = oct,

doi = "10.1109/CLOUD49709.2020.00013",

language = "English",

series = "IEEE International Conference on Cloud Computing, CLOUD",

publisher = "IEEE Computer Society",

pages = "22--24",

booktitle = "Proceedings - 2020 IEEE 13th International Conference on Cloud Computing, CLOUD 2020",

}

TY - GEN

T1 - Adaptive control channel traffic shaping for virtualized SDN in clouds

AU - Yoo, Yeonho

AU - Yang, Gyeongsik

AU - Kang, Minkoo

AU - Yoo, Chuck

N1 - Funding Information: ‡This work was partly supported by Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (No. 2015-0-00280, (SW Starlab) Next generation cloud infra-software toward the guarantee of performance and security SLA) and by Next Generation Engineering Researcher Program of National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT (No. NRF-2019H1D8A2105513).

PY - 2020/10

Y1 - 2020/10

N2 - As the number of tenants in clouds grows, virtualized SDN faces a challenge of control channel fairness as the control channels interfere with each other. This paper proposes an adaptive traffic shaping scheme for control channels called 'Sincon.' Through experiments, Sincon achieves traffic shaping for control channels and improves the variances of control channel throughputs and forwarding setup times up to 3.8 and 2.86 times, respectively.

AB - As the number of tenants in clouds grows, virtualized SDN faces a challenge of control channel fairness as the control channels interfere with each other. This paper proposes an adaptive traffic shaping scheme for control channels called 'Sincon.' Through experiments, Sincon achieves traffic shaping for control channels and improves the variances of control channel throughputs and forwarding setup times up to 3.8 and 2.86 times, respectively.

KW - Cloud network

KW - Control channel traffic

KW - Network virtualization

KW - SDN

KW - Traffic shaping

UR - http://www.scopus.com/inward/record.url?scp=85098561180&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85098561180&partnerID=8YFLogxK

U2 - 10.1109/CLOUD49709.2020.00013

DO - 10.1109/CLOUD49709.2020.00013

M3 - Conference contribution

AN - SCOPUS:85098561180

T3 - IEEE International Conference on Cloud Computing, CLOUD

SP - 22

EP - 24

BT - Proceedings - 2020 IEEE 13th International Conference on Cloud Computing, CLOUD 2020

PB - IEEE Computer Society

T2 - 13th IEEE International Conference on Cloud Computing, CLOUD 2020

Y2 - 18 October 2020 through 24 October 2020

ER -