Performance Study of Multi-access Edge Computing Deployment in a Virtualized Environment

Tambe, Supriya Dilip and Mandge, Yogesh and Franklin, Antony (2020) Performance Study of Multi-access Edge Computing Deployment in a Virtualized Environment. In: 3rd IEEE 5G World Forum, 5GWF 2020, 10-12 September 2020, Virtual, Bangalore.

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Abstract

Various real-time, latency-sensitive, and high-speed mobile applications are evolving as 5G applications. These applications are realized using Multi-access Edge Computing (MEC) and Network Function Virtualization (NFV) technologies in the 5G system. MEC platform, MEC service, and MEC application are the main components of an MEC Framework. NFV Orchestrator, Virtualized Infrastructure Manager (VIM), and virtualization technologies such as Virtual Machines (VM) and Containers are the main pillars of the NFV technology. In this paper, we study the impact of the virtualization technologies in the deployment of the MEC framework and its components while. We also study the impact of virtualization technologies on NFV and MEC KPIs such as onboarding time, instantiation time, MEC service and application response times. The experiments and its analysis show that containers perform better than VM to instantiate/terminate MEC components in the NFV framework. The observed MEC service KPIs show that the edge application's performance will be improved to meet the QoE of the applications irrespective of the virtualization technology used. These results can be used as a reference while deploying the MEC components based on their granular functionalities. © 2020 IEEE.

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IITH Creators:

IITH Creators	ORCiD
Franklin, Antony	https://orcid.org/0000-0002-1809-2025

Item Type:

Conference or Workshop Item (Paper)

Additional Information:

ACKNOWLEDGMENT This work was supported by the project ”Indigenous 5G Testbed” funded by the Department of Telecommunications (DoT), Government of India.

Uncontrolled Keywords:

MANO; MEC Framework; NFV; OpenStack; Virtualization Technologies

Subjects:

Computer science

Divisions:

Department of Computer Science & Engineering

Depositing User:

. LibTrainee 2021

Date Deposited:

16 Nov 2022 06:26

Last Modified:

16 Nov 2022 06:26