A connectionist approach to dynamic resource management for virtualised network functions

Mijumbi, Rashid and Hasija, Sidhant and Davy, Steven and Davy, Alan and Jennings, Brendan and Boutaba, Raouf (2017) A connectionist approach to dynamic resource management for virtualised network functions. In: 2016 12th International Conference on Network and Service Management, CNSM 2016 and Workshops, 3rd International Workshop on Management of SDN and NFV, ManSDN/NFV 2016, and International Workshop on Green ICT and Smart Networking, GISN 2016 :. 2016 12th International Conference on Network and Service Management, CNSM 2016 and Workshops, 3rd International Workshop on Management of SDN and NFV, ManSDN/NFV 2016, and International Workshop on Green ICT and Smart Networking, GISN 2016 . Institute of Electrical and Electronics Engineers Inc., CAN, pp. 1-9. ISBN 9783901882852

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Abstract

Network Functions Virtualisation (NFV) continues to gain attention as a paradigm shift in the way telecommunications services are deployed and managed. By separating Network Functions (NFs) from traditional middleboxes, NFV is expected to lead to reduced CAPEX and OPEX, and to more agile services. However, one of the main challenges to achieving these objectives is on how physical resources can be efficiently, autonomously, and dynamically allocated to Virtualised Network Functions (VNFs) whose resource requirements ebb and flow. In this paper, we propose a Graph Neural Network (GNN)-based algorithm which exploits Virtual Network Function Forwarding Graph (VNF-FG) topology information to predict future resource requirements for each Virtual Network Function Component (VNFC). The topology information of each VNFC is derived from combining its past resource utilisation as well as the modelled effect on the same from VNFCs in its neighbourhood. Our proposal has been evaluated using a deployment of a virtualised IP Multimedia Subsystem (IMS), and real VoIP traffic traces, with results showing an average prediction accuracy of 90%. Moreover, compared to a scenario where resources are allocated manually and/or statically, our proposal reduces the average number of dropped calls by at least 27% and improves call setup latency by over 29%.

Item Type:	Book Section
Additional Information:	Funding Information: This publication has emanated from research supported in part by a research grant from Science Foundation Ireland (SFI) and is co-funded under the European Regional Development Fund under Grant Number 13/RC/2077 Publisher Copyright: © 2016 IFIP.
Uncontrolled Keywords:	/dk/atira/pure/subjectarea/asjc/1700/1705
Departments or Groups:
Depositing User:	Admin SSL
Date Deposited:	19 Oct 2022 23:16
Last Modified:	12 Jul 2023 18:44
URI:	http://repository-testing.wit.ie/id/eprint/5054

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