Abstract

Aiming at the problem of network congestion and unbalanced load caused by a large amount of data capacity carried in elephant flow in the data center network, an elephant flow detection method based on SDN is proposed. This method adopts the autodetect upload (ADU) mechanism. ADU is divided into two parts: ADU-Client and ADU-Server, in which ADU-Client runs in the host computer and ADU-Server runs in the SDN controller. When the host sends the elephant flow, the ADU-Client generates a packet with forged source IP address and triggers the Packet_in message of the edge switch to report the information of the elephant flow to the SDN controller and the ADU-Server completes the elephant flow identification. Experimental results show that the ADU elephant flow detection mechanism can effectively detect elephant flow in the data center network, reduce detection time, and improve network performance.

Highlights

  • In the data center network, the problem of network link congestion and uneven load caused by elephant flow is becoming increasingly serious

  • Elephant flow detection time refers to the time required for an elephant flow to enter a network link to obtain information about this elephant flow. e correct detection rate of elephant flow is divided into two parts: the missing rate and the false reject rate

  • False reject rate refers to the proportion of the number of elephant flows misjudged by the mouse flow as a proportion of all elephant flows

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Summary

Introduction

In the data center network, the problem of network link congestion and uneven load caused by elephant flow is becoming increasingly serious. When an identified elephant flow data packet is sent to the network, the switch will match the flow table of the DSCP field and send this packet to the controller through the Packet_in message to report the elephant flow. Liu et al [10] proposed a traffic load balancing scheme based on software-defined networking (SDN) technology, using flow engineering to identify and manage elephant flows and using a weighted multipath routing algorithm to dispatch elephant flows to multiple roads. To reduce the detection time of the elephant flow, reduce the transmission delay of the network, and improve the link utilization while taking advantage of the SDN technology, this paper studies the elephant flow detection mechanism of the data center network.

SDN-Based Data Center Network
Experiments and Results
MB Threshold
Conclusion

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