Paper Info
Title
Smart Scaling of the 5G Core Network - An RNN-Based Approach.
Abstract
The upcoming mobile core network, which will be based on Virtual Network Functions (VNF), will face an increase of data traffic on both data and control planes. This is due to the increase of the number of connected devices and the newly 5G supported-services like IoT, Connected Health Care etc. Therefore dynamic and accurate scalability techniques should be envisioned in order to answer the needs, in term of resource provisioning, without degrading the Quality Of Service (QoS) already offered by hardware based core networks. Although provisioning new resources is easier as it is a matter of software deployment, the strategy to use (when to scale and how much to scale) remains complex. In this paper we propose scaling techniques based on neural networks to forecast the upcoming load. Hence scheduling the resource provisioning should be in a manner that all the needed resources will be deployed and active when the load increases. In the same way, it will scale-in the unneeded resources when the traffic load decreases. The proposal is tested via discrete event simulations using a traffic load dataset provided by a Network Operator. The results show clearly the robustness of our proposal compared to a threshold-based scaling technique.
Year
DOI
Venue
2018
10.1109/GLOCOM.2018.8647590
IEEE Global Communications Conference
Keywords
Field
DocType
5G,Scaling,Load Balancing,Mobile Core Network,Prediction,Neural Network
Virtual network,Core network,Scheduling (computing),Load balancing (computing),Computer science,Quality of service,Computer network,Robustness (computer science),Provisioning,Scalability
Conference
ISSN
Citations 
PageRank 
2334-0983
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Imad Alawe101.01
Y. Hadjadj-Aoul2374.28
Adlen Ksentini3108593.20
Philippe Bertin4649.44
César Viho541438.73
davy darche601.01