Dynamic UPF placement and chaining reconfiguration in 5G networks

Leyva-Pupo, I., Cervelló-Pastor, C., Anagnostopoulos, C. and Pezaros, D. P. (2022) Dynamic UPF placement and chaining reconfiguration in 5G networks. Computer Networks, 215, 109200. (doi: 10.1016/j.comnet.2022.109200)

Abstract

Network function virtualization (NFV) and multi-access edge computing (MEC) have become two crucial pillars in developing 5G and beyond networks. NFV promises cost-saving and fast revenue generation through dynamic instantiation and the scaling of virtual network functions (VNFs) according to time-varying service demands. Additionally, MEC provides considerable reductions in network response time and backhaul traffic since network functions and server applications can be deployed close to users. Nevertheless, the placement and chaining of VNFs at the network edge is challenging due to numerous aspects and attendant trade-offs. This paper addresses the problem of dynamic user plane function placement and chaining reconfiguration (UPCR) in a MEC environment to cope with user mobility while guaranteeing cost reductions and acceptable quality of service (QoS). The problem is formalized as a multi-objective integer linear programming model to minimize multiple cost components involved in the UPCR procedure. We propose a heuristic algorithm called dynamic priority and cautious UPCR (DPC-UPCR) to reduce the solution time complexity. Additionally, we devise a scheduler mechanism based on optimal stopping theory to determine the best reconfiguration time according to instantaneous values of latency violations and a pre-established QoS threshold. Our detailed simulation results evidence the efficiency of the proposed approaches. Specifically, the DPC-UPCR provides near-optimal solutions, within 15% of the optimum in the worst case, in significantly shorter times than the mathematical model. Moreover, the proposed scheduling method outperforms two scheduler baseline solutions regarding the number of reconfiguration events and QoS levels.

• Item Type: Articles
• Additional Information: This work has been supported by the Agencia Estatal de Investigación of Ministerio de Ciencia e Innovación of Spain under project PID2019-108713RB-C51/ MCIN/AEI/ 10.13039/501100011033 and through a predoctoral FPI scholarship. Additionally, this work was supported in part by the PETRAS National Centre of Excellence for IoT Systems Cybersecurity, which has been funded by the UK EPSRC under grant number EP/S035362/1.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Leyva Pupo, Irian and Anagnostopoulos, Dr Christos and Pezaros, Professor Dimitrios

Creator Roles

Leyva Pupo, I.: Conceptualization, Formal analysis, Methodology, Data curation, Validation, Visualization, Software, Writing – original draft
Anagnostopoulos, C.: Conceptualization, Formal analysis, Validation, Methodology, Supervision, Writing – review and editing
Pezaros, D.: Conceptualization, Formal analysis, Validation, Methodology, Supervision, Writing – review and editing, Funding acquisition, Project administration

• Authors: Leyva-Pupo, I., Cervelló-Pastor, C., Anagnostopoulos, C., and Pezaros, D. P.
• College/School: College of Science and Engineering > School of Computing Science
• Journal Name: Computer Networks
• Publisher: Elsevier
• ISSN: 1389-1286
• ISSN (Online): 1872-7069
• Published Online: 20 July 2022
• Copyright Holders: Copyright © 2022 The Authors
• First Published: First published in Computer Networks 215: 109200
• Publisher Policy: Reproduced under a Creative Commons License