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Adaptive and Latency-aware Load Balancing for Control Plane Traffic in the 4G/5G Core
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (Distributed Systems and Communications Research Group (DISCO))ORCID iD: 0000-0002-9399-8425
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (Distributed Systems and Communications Research Group (DISCO))ORCID iD: 0000-0003-4147-9487
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (Distributed Systems and Communications Research Group (DISCO))ORCID iD: 0000-0001-9194-010X
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (Distributed Systems and Communications Research Group (DISCO))ORCID iD: 0000-0001-7311-9334
2021 (English)In: 2021 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit), IEEE Communications Society, 2021Conference paper, Published paper (Refereed)
Abstract [en]

For many years, the continuous proliferation of mobile devices and their applications generate a surge of signaling traffic in the control plane of the mobile packet core network. As a consequence, the control plane will potentially become a bottleneck if not properly managed. We focus on the load balancing of a virtualized and distributed Mobility Management Entity (vMME), which is the key control plane element in the 4G and 5G non-standalone cores. Most of existing works use the simple and static load balancing approaches such as roundrobin and consistent hashing, which do not work well in a heterogeneous environment. In this paper, we developed three adaptive algorithms in which the balancing decision takes into account the dynamics of the system such as the vMME load, the completion time of a request served by a vMME, and the number of pending requests queued at a vMME. The evaluation of our three proposed load-balancing algorithms in an Open5GCore testbed suggests that the latency-aware scheme helps shorten the completion time of the signaling requests by up to five times the static and dynamic schemes in those cases the link delay between the load balancer and the vMMEs differ significantly.

Place, publisher, year, edition, pages
IEEE Communications Society, 2021.
Keywords [en]
5G Core, Load Balancing, Latency-Aware
National Category
Telecommunications
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-83759DOI: 10.1109/EuCNC/6GSummit51104.2021.9482513Scopus ID: 2-s2.0-85112639551OAI: oai:DiVA.org:kau-83759DiVA, id: diva2:1546821
Conference
The 2021 Joint EuCNC & 6G Summit, Porto, Portugal, June 8-11, 2021.
Projects
High Quality Networked Services in a Mobile World (HITS)
Funder
Knowledge FoundationAvailable from: 2021-04-23 Created: 2021-04-23 Last updated: 2022-03-18Bibliographically approved
In thesis
1. Towards a Scalable and Low-Latency Softwarized Mobile Packet Core Network
Open this publication in new window or tab >>Towards a Scalable and Low-Latency Softwarized Mobile Packet Core Network
2021 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The mobile packet core – a central part of the overall mobile cellular network – has a long history of evolution. Through the years, its architecture has been drastically changed to meet the demand coming from the fast growth in the number of devices as well as the introduction of new types of applications and services. On one hand, the number of new devices and subscribers keeps increasing at an unprecedented rate, which can still give rise to scalability issues in the mobile packet core if it is not properly managed. On the other hand, the introduction of new types of services brings with it a new set of requirements, such as low-latency and high reliability. The network softwarization is widely considered as a promising approach to address these two challenges.

This thesis focuses on enhancing the scalability of a softwarized mobile packet core network for 5G and beyond, and the communication latency it provides. Moreover, the thesis provides an extensive survey of existing softwarized mobile packet core network solutions, identifying important questions and gaps for future research. This thesis also explores the possibility of leveraging the network softwarization concept to design a softwarized mobile packet core network to support multicast and broadcast services. In order to tackle the scalability issue in a softwarized mobile packet core, the thesis proposes several dynamic and adaptive load-balancing algorithms to efficiently manage the traffic load in both the control and the user plane. These load-balancing algorithms take into account different factors such as the current load of virtualized network functions and the estimation of the communication latency. On the latency aspect, the thesis studies the feasibility of using a softwarized mobile packet core for delivering time-critical messages in a smart-grid environment, and proposes several deployable communication solutions to support the study.

Place, publisher, year, edition, pages
Karlstad: Karlstads universitet, 2021. p. 44
Series
Karlstad University Studies, ISSN 1403-8099 ; 2021:16
Keywords
Mobile Packet Core, Evolved Packet Core, 5G, SDN, NFV, Scalability, Control Plane, User Plane, MME, UPF, VPP, Load Balancing, Auto-Scaling, Time-Critical, Low-Latency, Smart Grid, GOOSE
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-83734 (URN)978-91-7867-211-0 (ISBN)978-91-7867-221-9 (ISBN)
Public defence
2021-06-07, Zoom, 13:00 (English)
Opponent
Supervisors
Projects
HITSH2020 5Genesis
Funder
Knowledge Foundation, 4707
Note

Article 6 part of thesis as manuscript, now published.

Available from: 2021-05-17 Created: 2021-04-22 Last updated: 2022-03-18Bibliographically approved

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Nguyen, Van-GiangGrinnemo, Karl-JohanTaheri, JavidBrunström, Anna

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