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Energy Efficient NFV Orchestration using Machine Learning

Lead Research Organisation: University of Glasgow
Department Name: School of Computing Science

Abstract

"With the development of 5G technology, we now see the gradual realisation of broadband,
ultra-reliable, and zero latency services. Network Function Virtualization (NFV) and Mobile
Edge Computing (MEC) are important 5G elements, and an NFV enabled MEC network
allows for movement of the Virtual Network Function (VNFs) from a distant cloud to an edge
network. At the same time, due to the rapid increment of network traffic demands and a focus
of attention on energy consumption issues, there is a trend for much higher energy
efficiency requirements. In order to satisfy such requirements we will consider the
deployment of VNFs as a network resource optimisation problem, aiming to allocate limited CPU, memory, and bandwidth while minimising the network-widew energy footprint of the ICT infrastructure."

People

ORCID iD

Jinming Yang (Student)

Publications

10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/R513222/1 30/09/2018 29/09/2023
2907997 Studentship EP/R513222/1 23/01/2023 23/07/2026 Jinming Yang
EP/W524359/1 30/09/2022 29/09/2028
2907997 Studentship EP/W524359/1 23/01/2023 23/07/2026 Jinming Yang