Proceedings of the 2nd Annual International Conference on Electronics, Electrical Engineering and Information Science (EEEIS 2016)

An Efficient Approximation Algorithm for Traffic Engineering in Software Defined Networks

Authors
Gang Wang, Gang Feng, Shuang Qin, Mu Yan, Yan-Tao Guo
Corresponding Author
Gang Wang
Available Online December 2016.
DOI
10.2991/eeeis-16.2017.85How to use a DOI?
Keywords
Traffic Engineering; multi-commodity flow; FPTAS.
Abstract

In this paper, we focus on the efficient algorithm for solving the multi-commodity flow problems involved in TE and develop an improved approximation algorithm (i-FPTAS) based on the Fully Polynomial Time Approximation Scheme (FPTAS), with aim of greatly improving computational efficiency without compromising traffic load balancing performance. Numerical results shows that i-FPTAS can achieve close-optimal approximation solution which is much better than that of FPATS with the same approximate parameter, and increasing the approximate parameter of i-FPTAS can lower computational complexity with little loss on close-optimality.

Copyright
© 2017, 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 2nd Annual International Conference on Electronics, Electrical Engineering and Information Science (EEEIS 2016)
Series
Advances in Engineering Research
Publication Date
December 2016
ISBN
10.2991/eeeis-16.2017.85
ISSN
2352-5401
DOI
10.2991/eeeis-16.2017.85How to use a DOI?
Copyright
© 2017, 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  - Gang Wang
AU  - Gang Feng
AU  - Shuang Qin
AU  - Mu Yan
AU  - Yan-Tao Guo
PY  - 2016/12
DA  - 2016/12
TI  - An Efficient Approximation Algorithm for Traffic Engineering in Software Defined Networks
BT  - Proceedings of the 2nd Annual International Conference on Electronics, Electrical Engineering and Information Science (EEEIS 2016)
PB  - Atlantis Press
SP  - 697
EP  - 703
SN  - 2352-5401
UR  - https://doi.org/10.2991/eeeis-16.2017.85
DO  - 10.2991/eeeis-16.2017.85
ID  - Wang2016/12
ER  -