Optimizing Resource Fragmentation in Virtual Network Function Placement Using Deep Reinforcement Learning

Optimizing Resource Fragmentation in Virtual Network Function Placement Using Deep Reinforcement Learning

In the 6G wireless era, the strategical deployment of Virtual Network Functions (VNFs) within a network infrastructure that optimizes resource utilization while fulfilling performance criteria is critical for successfully implementing the Network Function Virtualization (NFV) paradigm across the Edg...

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Bibliographic Details
Main Authors: Ramy Mohamed, Marios Avgeris, Aris Leivadeas, Ioannis Lambadaris
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Transactions on Machine Learning in Communications and Networking
Subjects:
Resource fragmentation
neural combinatorial optimization
reinforcement learning
service function chaining
virtual network function placement
5G
Online Access:https://ieeexplore.ieee.org/document/10695455/
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