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Article . 2018 . Peer-reviewed
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Towards Resource-Efficient Service Function Chain Deployment in Cloud-Fog Computing

Authors: Dongcheng Zhao; Dan Liao; Gang Sun 0001; Shizhong Xu;

Towards Resource-Efficient Service Function Chain Deployment in Cloud-Fog Computing

Abstract

Most studies on network function virtualization are based on cloud computing environments. Fog computing has been proposed as a supplement to cloud computing. When deploying the service function chain (SFC), the consumption of network resources can be effectively reduced by taking advantage of a combination of cloud and fog computing. However, few SFC studies are based on fog computing environments. Moreover, the problem of combining SFCs for the support of live online services to reduce network congestion and save network resources has not been considered. To effectively take advantage of cloud-fog computing and thus achieve the goal of saving resources and reducing network congestion, in this paper, we study the SFC combination and deployment problem in cloud-fog computing environments. To solve this problem, we present an efficient SFC combination and deployment algorithm. Finally, we conduct extensive simulations to evaluate the performance of our proposed algorithm. The results show that our proposed algorithm can effectively reduce network resource consumption and effectively resolve network congestion caused by live online services.

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Keywords

combination, service function chain, deployment, network function virtualization, Electrical engineering. Electronics. Nuclear engineering, Cloud-fog computing, TK1-9971

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Top 10%
Top 10%
Top 10%
gold