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Openflow Based Dynamic Flow Scheduling with Multipath for Data Center Networks

Haisheng Yu1, Heng Qi1, Keqiu Li1, Jianhui Zhang1,Peng Xiao2, Xun Wang1
1 School of Computer Science and Technology, Dalian University of Technology, Dalian, China
2 School of Information Science & Engineering, Dalian Polytech University, Dalian, China

Computer Systems Science and Engineering 2018, 33(4), 251-258. https://doi.org/10.32604/csse.2018.33.251

Abstract

The routing mechanism in Data Center networks can affect network performance and latency significantly. Hash-based method, such as ECMP (Equal-Cost Multi-Path), has been widely used in Data Center networks to fulfill the requirement of load balance. However, ECMP statically maps one flow to a path by a hash method, which results in some paths overloaded while others remain underutilized. Some dynamic flow scheduling schemes choose the most underutilized link as the next hop to better utilize the network bandwidth, while these schemes lacks of utilizing the global state of the network. To achieve high bandwidth utilization and low latency, we present a dynamic flow scheduling mechanism based on OpenFlow protocol which enables monitoring the global network information by a centralized controller. Depending on the network statistics obtained by the OpenFlow controller, the routing algorithm chooses the best path for the flow. Because there are two kinds of flows in a Data Center, short-lived flows and long-lived flows, we proposed two different algorithms for them. The implementation uses pox as OpenFlow controller and mininet as the network emulator. The evaluation results demonstrate that our dynamic flow scheduling algorithm is effective and can achieve high link utilization.

Keywords

Data Center; Software-defined Networking; ECMP; DLB; FC-DLB

Cite This Article

H. Yu, H. Qi, K. Li, J. Zhang, P. Xiao et al., "Openflow based dynamic flow scheduling with multipath for data center networks," Computer Systems Science and Engineering, vol. 33, no.4, pp. 251–258, 2018.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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