A Model for Virtualized Network Function Placement with Hardware Acceleration Support

Yuxiang HU; Hongwei FAN; Julong LAN; Tong DUAN

doi:10.11999/JEIT180861

Volume 41 Issue 8

Aug. 2019

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Yuxiang HU, Hongwei FAN, Julong LAN, Tong DUAN. A Model for Virtualized Network Function Placement with Hardware Acceleration Support[J]. Journal of Electronics & Information Technology, 2019, 41(8): 1893-1901. doi: 10.11999/JEIT180861

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Yuxiang HU, Hongwei FAN, Julong LAN, Tong DUAN. A Model for Virtualized Network Function Placement with Hardware Acceleration Support[J]. Journal of Electronics & Information Technology, 2019, 41(8): 1893-1901. doi: 10.11999/JEIT180861

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A Model for Virtualized Network Function Placement with Hardware Acceleration Support

doi: 10.11999/JEIT180861

National Digital Switching System Engineering & Research Center, Zhengzhou 450002, China

Funds: The National Network Security Special Program of China (2017YFB0803204), The National Natural Science Foundation of China (61521003)

Received Date: 2018-09-04
Rev Recd Date: 2019-01-04

Available Online: 2019-01-16

Publish Date: 2019-08-01

Abstract

Abstract

In order to deal with the limited capacity of Virtualized Network Function (VNF), hardware acceleration resources are adopted in Software-Defined Networking and Network Function Virtualization (SDN/NFV) architecture. The deployment of hardware acceleration resources enables VNF to provide service guarantees for increasing data traffic. To overcome the ignorance of the requirements for VNF with high processing throughput in service chain in existing researches, a model for VNF placement with hardware acceleration support is proposed. Based on the bearing characteristics of hardware acceleration resources, the model prioritizes the reuse of acceleration resources in the switch under the optimal placement of VNF without acceleration to commercial servers. The mapping correlation between hardware acceleration resources and VNF is flexibly adjusted according to the requirements of network services. Simulation results show that the proposed model can bear more service flows and meet the high processing throughput needs of service chains than typical policies in the case of the same amount of resources, which improves effectively the resource utilization of the acceleration hardware deployed in the network.

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References

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