Towards AI-enabled Microservice Architecture for Network Function Virtualization

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Nekovee, Maziar, Sharma, Sachin, Uniyal, Navdeep, Nag, Avishek, Nejabati, Reza and Simeonidou, Dimitra (2020) Towards AI-enabled Microservice Architecture for Network Function Virtualization. In: IEEE COMNET, February 2020, Virtual Conference.

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Official URL: https://www.researchgate.net/publication/339209735...

Abstract

Abstract—Network Function Virtualization (NFV) enables operators to flexibly deploy network services on commodity servers in an on-demand and agile manner. This has recently attracted significant attention from industry and academia. However, there are important challenges for NFV deployment, including performance bottlenecks, degraded fault tolerance, upgrading complexities, and security threats. To overcome these challenges, the microservice approach, which has been applied successfully in cloud computing, has motivated the research communities to apply its principles in NFV domains. In this paper, we first compare the challenges of employing the microservices approach in both the cloud computing and the NFV domains, and then discuss the need for AI-enabled microservices architecture for NFV. Performance evaluation of the microservices approach in NFV is performed on bare-metal machine setups. The results compare the pros and cons of the microservice approach and show the need for AI to handle the complex decisions associated with decomposing network functions into microservices or vice versa. We also propose an AI-enabled microservice architecture and present its potential use cases for personalized live streaming, smart public safety, and enterprise VPN (Virtual Private Network). Open questions and future work are also presented.
Index Terms—NFV, Cloud Computing, Artificial Intelligence, Microservices

Item Type:	Conference or Workshop Item (Paper)
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > T Technology (General)
Divisions:	School of Computing > Staff Research and Publications
Depositing User:	Dan English
Date Deposited:	13 Oct 2020 11:08
Last Modified:	13 Oct 2020 11:08
URI:	https://norma.ncirl.ie/id/eprint/4348

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