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Low frequency assist for mmWave backhaul - the case for SDN resiliency mechanisms
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (Distributed systems and communication, DISCO)ORCID iD: 0000-0001-7358-8675
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Computer Science. (Distributed systems and communication, DISCO)ORCID iD: 0000-0002-9446-8143
2017 (English)In: Communications Workshops (ICC Workshops), 2017 IEEE International Conference on, 2017Conference paper, Published paper (Refereed)
Abstract [en]

In 5G, network densification is a major concern for operators. When a massive amount of small cells are deployed, the backhaul capacity is crucial and researchers are exploring the use of high frequency bands such as 28, 60 or even 140 GHz because of the large portion of spectrum that is available. Unfortunately, such mmWave links frequently change their capacity due to blocking and weather phenomena which makes it challenging to design stable multihop backhaul networks using those frequency bands. In this paper, we investigate the use of Software Defined Networking (SDN) for the operation and control of wireless backhaul networks. We explore different ways how SDN resiliency mechanisms such as FastFailover Groups can be used to mitigate disruptive connectivity in the multihop operation due to mmWave links frequently failing. We also demonstrate a clear benefit for using low frequency assist mode, where the small cell has an additional stable LTE uplink to the eNB that is used should the mmWave backhaul links fail. Our experiments using a network emulator show that such SDN based local repair mechanisms can significantly reduce the packet loss rate inside the mmWave backhaul mesh, which can be further reduced with an LTE assisted Failover.

Place, publisher, year, edition, pages
2017.
Series
IEEE Xplore, ISSN 2474-9133
Keywords [en]
5G mobile communication, Long Term Evolution, software defined networking, telecommunication network reliability
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-65609DOI: 10.1109/ICCW.2017.7962658ISBN: 978-1-5090-1526-9 (print)ISBN: 978-1-5090-1525-2 (electronic)OAI: oai:DiVA.org:kau-65609DiVA, id: diva2:1174268
Conference
IEEE International Conference on Communications Workshops (ICC Workshops), 21-25 May 2017. Paris, France
Available from: 2018-01-15 Created: 2018-01-15 Last updated: 2018-06-27Bibliographically approved
In thesis
1. SDN-Enabled Resiliency in Computer Networks
Open this publication in new window or tab >>SDN-Enabled Resiliency in Computer Networks
2018 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

In computer networking, failures, such as breaking equipment, cable cuts, power failures and human errors continuously cause communication interruptions. Such failures may result in dissatisfied customers, loss of product reputation, violation of SLAs and even critical failures in industrial systems. SDN, which logically centralizes the control plane, is an emerging technology in computer networking. The global view provided by the SDN controller can be used to reconfigure the network in case of a link failure. However, this reconfiguration may take too long for high availability networks. With the introduction of proactive link repair, backup paths are preinstalled in the forwarding devices, reducing path recovery time.

This thesis addresses the usage of SDN to provide resiliency in high availability networks. First, we consider how SDN can be used for increasing the reliability of ICNs. Second, we investigate how similar technologies could be applied to deal with fast channel attenuation and resulting outage in mmWave backhaul networks. Finally, we look at CloudMAC-based Wireless LAN, and how SDN-enabled QoS improvements could improve connection reliability.

Abstract [en]

In computer networking, failures, such as breaking equipment, cable cuts, power failures and human errors continuously cause communication interruptions. Such failures may result in dissatisfied customers, loss of product reputation, violation of Service Level Agreements and even critical failures in industrial systems. Recently, the concept of Software Defined Networking (SDN) was introduced. SDN opens up and centralizes the control plane, which allows designing networks more resilient to failures.

In this thesis, we address the usage of SDN in order to provide resiliency in high availability networks. First, we consider how SDN enabled, proactive failure recovery can be used to provide the reliability required in Industrial Control Networks (ICNs). We also investigate how the same approach could be applied to mmWave backhaul networks to cope with fast channel attenuation and the resulting outage. Through extensive experiments, we can demonstrate an increase in reliability for both ICNs and mmWave backhaul networks. Second, we look at CloudMAC-based Wireless LAN, and how SDN-enabled traffic control algorithms could improve connection reliability. Through our experiments we can show that both discriminatory and non-discriminatory algorithms significantly increase the connection reliability. In combination, these results serve to strengthen the image of SDN as a provider of resilient, high-availability networks.

Place, publisher, year, edition, pages
Karlstad: Karlstads universitet, 2018. p. 24
Series
Karlstad University Studies, ISSN 1403-8099 ; 2018:17
Keywords
networking, sdn, openflow, resiliency, icn, mmwave, 5g, wlan
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-66992 (URN)978-91-7063-848-0 (ISBN)978-91-7063-943-2 (ISBN)
Presentation
2018-05-11, 1B 309 Sjöström, Universitetsgatan 2, Karlstad, 10:15 (English)
Opponent
Supervisors
Available from: 2018-04-20 Created: 2018-04-12 Last updated: 2018-04-30Bibliographically approved

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Vestin, JonathanKassler, Andreas

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