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Efficient OpenFlow based Inbound Load Balancing for Enterprise Networks
Author(s) -
Guodong Wang,
Peng Liu,
Yanxiao Zhao,
Jun Li,
Min Song
Publication year - 2018
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2018.03.082
Subject(s) - computer science , openflow , emulation , load balancing (electrical power) , distributed computing , computer network , scheduling (production processes) , quality of service , schedule , flexibility (engineering) , software defined networking , enterprise private network , operating system , operations management , geometry , mathematics , statistics , grid , economics , economic growth
Inbound load balancing plays an important role in improving the quality of experience for enterprise networks. Traditional traffic engineering approaches fail to achieve fine-grained inbound load balancing because they have limited capability of obtaining detailed network status and lack flexibility for traffic flow scheduling. In this paper, we adopt OpenFlow to achieve effective inbound load balancing. The potential of implementing OpenFlow in an enterprise network is explored to schedule traffic among different inbound links. We also investigate how to avoid frequent scheduling and the feasibility when applying this approach in real networks. In order to evaluate the proposed approach, an emulation platform is developed based on Mininet, POX and Open vSwitch. Emulation is conducted based on an actual network topology. Emulation results verify that the proposed approach is able to achieve effective load balancing for enterprise networks and avoid unnecessary flow scheduling.

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