Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology

A Load Balancing Model based on Load-aware for Distributed Controllers

Authors
Fengjun Shang, Wenjuan Gong
Corresponding Author
Fengjun Shang
Available Online March 2016.
DOI
10.2991/icmmct-16.2016.45How to use a DOI?
Keywords
Software-Defined Networking; Load-aware; Load Balancing; Failure Recovery
Abstract

Software-Defined Networking (SDN) is a new paradigm that decouples the control plane from data plane. But with the continuous expansion of the network scale, a single controller faces with scalability issues and may trigger a single point of failure. It is important to take into account the scalability of the control plane and how to balance the load of multiple controllers. In this paper, we study and analyzed the architecture model of multiple controllers and then proposed a load balancing model based on load-aware for distributed controllers which can flexibly adjust the flow-requests handled by each controller based on the flow-request, and resolved the single point of failure through fast recovery of failure.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology
Series
Advances in Engineering Research
Publication Date
March 2016
ISBN
10.2991/icmmct-16.2016.45
ISSN
2352-5401
DOI
10.2991/icmmct-16.2016.45How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Fengjun Shang
AU  - Wenjuan Gong
PY  - 2016/03
DA  - 2016/03
TI  - A Load Balancing Model based on Load-aware for Distributed Controllers
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology
PB  - Atlantis Press
SP  - 239
EP  - 243
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-16.2016.45
DO  - 10.2991/icmmct-16.2016.45
ID  - Shang2016/03
ER  -