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On Analyzing the Trade-Off Between Over-Commitment Ratio and Quality of Service in NFV Datacenter

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11814))

Abstract

Network Function Virtualization (NFV) is one of the key technologies in 5G. It inherits virtualization technology in cloud computing and promises to bring many benefits for industry such as saving energy and reducing capital expenditure. Resource over-commitment is a significant technique of virtualization to fully utilize the resources of a cloud datacenter. Deploying VNFs with difference over-commitment ratios in an NFV datacenter leads to different results of the number of servers used and the order of VNFs placed in each physical server. This also affects Quality of Service (QoS) and energy consumption in the NFV datacenter. However, to the best of our knowledge, there has been no study to find exactly how much resource over-commitment is sufficient to meet the QoS while reducing the energy used in an NFV datacenter. In this paper, we analyze and evaluate the effect of CPU over-commitment ratio in VNF placement problem while considering the QoS and energy efficiency for NFV datacenters. After exhausting simulations, we have found out a proper value for CPU over-commitment ratio for NFV datacenters. By employing that ratio, an NFV datacenter could reduce up to 16.8% total power consumption compared with the others not using the over-provisioning technique.

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Acknowledgment

This research was supported in part by Korean government, under by AI Graduate School Support Program (No. 2019-0-00421) supervised by the Ministry of Science and ICT (MSIT) and ICT Consilience Creative program (IITP-2019-2015-0-00742) supervised by the Institute of Information & Communications Technology Planning & Evaluation (IITP), respectively.

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Correspondence to Moonseong Kim or Hyunseung Choo .

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Tran, MH., Dang, TB., Van Vo, V., Le, DT., Kim, M., Choo, H. (2019). On Analyzing the Trade-Off Between Over-Commitment Ratio and Quality of Service in NFV Datacenter. In: Dang, T., Küng, J., Takizawa, M., Bui, S. (eds) Future Data and Security Engineering. FDSE 2019. Lecture Notes in Computer Science(), vol 11814. Springer, Cham. https://doi.org/10.1007/978-3-030-35653-8_21

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  • DOI: https://doi.org/10.1007/978-3-030-35653-8_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-35652-1

  • Online ISBN: 978-3-030-35653-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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